{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import time\n",
    "from matplotlib import pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "243.09044\n"
     ]
    }
   ],
   "source": [
    "start = time.clock()\n",
    "train = pd.read_csv(\"train\")\n",
    "elapse = time.clock() - start\n",
    "print(elapse)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the shape of the train is :\n",
      "(40428967, 24)\n"
     ]
    }
   ],
   "source": [
    "print('the shape of the train is :')\n",
    "print(train.shape)\n",
    "# print('the shape of the test is :')\n",
    "# print(test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>click</th>\n",
       "      <th>hour</th>\n",
       "      <th>C1</th>\n",
       "      <th>banner_pos</th>\n",
       "      <th>site_id</th>\n",
       "      <th>site_domain</th>\n",
       "      <th>site_category</th>\n",
       "      <th>app_id</th>\n",
       "      <th>app_domain</th>\n",
       "      <th>...</th>\n",
       "      <th>device_type</th>\n",
       "      <th>device_conn_type</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <td>-1</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.000017e+19</td>\n",
       "      <td>0</td>\n",
       "      <td>14102100</td>\n",
       "      <td>1005</td>\n",
       "      <td>0</td>\n",
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       "      <td>7801e8d9</td>\n",
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       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.000037e+19</td>\n",
       "      <td>0</td>\n",
       "      <td>14102100</td>\n",
       "      <td>1005</td>\n",
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       "      <td>7801e8d9</td>\n",
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       "      <td>320</td>\n",
       "      <td>50</td>\n",
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       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>100084</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.000064e+19</td>\n",
       "      <td>0</td>\n",
       "      <td>14102100</td>\n",
       "      <td>1005</td>\n",
       "      <td>0</td>\n",
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       "      <td>100084</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.000068e+19</td>\n",
       "      <td>0</td>\n",
       "      <td>14102100</td>\n",
       "      <td>1005</td>\n",
       "      <td>1</td>\n",
       "      <td>fe8cc448</td>\n",
       "      <td>9166c161</td>\n",
       "      <td>0569f928</td>\n",
       "      <td>ecad2386</td>\n",
       "      <td>7801e8d9</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>18993</td>\n",
       "      <td>320</td>\n",
       "      <td>50</td>\n",
       "      <td>2161</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>-1</td>\n",
       "      <td>157</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             id  click      hour    C1  banner_pos   site_id site_domain  \\\n",
       "0  1.000009e+18      0  14102100  1005           0  1fbe01fe    f3845767   \n",
       "1  1.000017e+19      0  14102100  1005           0  1fbe01fe    f3845767   \n",
       "2  1.000037e+19      0  14102100  1005           0  1fbe01fe    f3845767   \n",
       "3  1.000064e+19      0  14102100  1005           0  1fbe01fe    f3845767   \n",
       "4  1.000068e+19      0  14102100  1005           1  fe8cc448    9166c161   \n",
       "\n",
       "  site_category    app_id app_domain ...  device_type device_conn_type    C14  \\\n",
       "0      28905ebd  ecad2386   7801e8d9 ...            1                2  15706   \n",
       "1      28905ebd  ecad2386   7801e8d9 ...            1                0  15704   \n",
       "2      28905ebd  ecad2386   7801e8d9 ...            1                0  15704   \n",
       "3      28905ebd  ecad2386   7801e8d9 ...            1                0  15706   \n",
       "4      0569f928  ecad2386   7801e8d9 ...            1                0  18993   \n",
       "\n",
       "   C15  C16   C17  C18  C19     C20  C21  \n",
       "0  320   50  1722    0   35      -1   79  \n",
       "1  320   50  1722    0   35  100084   79  \n",
       "2  320   50  1722    0   35  100084   79  \n",
       "3  320   50  1722    0   35  100084   79  \n",
       "4  320   50  2161    0   35      -1  157  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                  float64\n",
       "click                 int64\n",
       "hour                  int64\n",
       "C1                    int64\n",
       "banner_pos            int64\n",
       "site_id              object\n",
       "site_domain          object\n",
       "site_category        object\n",
       "app_id               object\n",
       "app_domain           object\n",
       "app_category         object\n",
       "device_id            object\n",
       "device_ip            object\n",
       "device_model         object\n",
       "device_type           int64\n",
       "device_conn_type      int64\n",
       "C14                   int64\n",
       "C15                   int64\n",
       "C16                   int64\n",
       "C17                   int64\n",
       "C18                   int64\n",
       "C19                   int64\n",
       "C20                   int64\n",
       "C21                   int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.dtypes\n",
    "#一共9个非数值特征，15个数值特征，click是ground truth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count                   40428967\n",
       "unique                  40428967\n",
       "top       3.4997041898509317e+18\n",
       "freq                           1\n",
       "Name: id, dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.id.astype(str).describe()\n",
    "#发现没有重复的ID特征，只是一个样本标识，可以直接删除"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#确定训练数据集的X和Y\n",
    "train_X = train.drop(['id','click'],axis = 1)\n",
    "train_Y = train.click"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#删除train，节省内存空间\n",
    "del train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>hour</th>\n",
       "      <th>C1</th>\n",
       "      <th>banner_pos</th>\n",
       "      <th>site_id</th>\n",
       "      <th>site_domain</th>\n",
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       "      <th>device_ip</th>\n",
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       "      <th>count</th>\n",
       "      <td>40428967</td>\n",
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       "      <td>a99f214a</td>\n",
       "      <td>6b9769f2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>447783</td>\n",
       "      <td>37140632</td>\n",
       "      <td>29109590</td>\n",
       "      <td>14596137</td>\n",
       "      <td>15131739</td>\n",
       "      <td>16537234</td>\n",
       "      <td>25832830</td>\n",
       "      <td>27237087</td>\n",
       "      <td>26165592</td>\n",
       "      <td>33358308</td>\n",
       "      <td>208701</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            hour        C1 banner_pos   site_id site_domain site_category  \\\n",
       "count   40428967  40428967   40428967  40428967    40428967      40428967   \n",
       "unique       240         7          7      4737        7745            26   \n",
       "top     14102209      1005          0  85f751fd    c4e18dd6      50e219e0   \n",
       "freq      447783  37140632   29109590  14596137    15131739      16537234   \n",
       "\n",
       "          app_id app_domain app_category device_id device_ip  \n",
       "count   40428967   40428967     40428967  40428967  40428967  \n",
       "unique      8552        559           36   2686408   6729486  \n",
       "top     ecad2386   7801e8d9     07d7df22  a99f214a  6b9769f2  \n",
       "freq    25832830   27237087     26165592  33358308    208701  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#样本的特征应该都是category，为了方便统计全部转成string进行分析\n",
    "column_list = train_X.columns\n",
    "train_X[column_list[:11]].astype(str).describe()\n",
    "#为了显示全部数据，将column分为2个部分"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>device_model</th>\n",
       "      <th>device_type</th>\n",
       "      <th>device_conn_type</th>\n",
       "      <th>C14</th>\n",
       "      <th>C15</th>\n",
       "      <th>C16</th>\n",
       "      <th>C17</th>\n",
       "      <th>C18</th>\n",
       "      <th>C19</th>\n",
       "      <th>C20</th>\n",
       "      <th>C21</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>count</th>\n",
       "      <td>40428967</td>\n",
       "      <td>40428967</td>\n",
       "      <td>40428967</td>\n",
       "      <td>40428967</td>\n",
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       "      <th>unique</th>\n",
       "      <td>8251</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
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       "      <td>4</td>\n",
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       "      <td>60</td>\n",
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       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>8a4875bd</td>\n",
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       "      <td>1722</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>-1</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>2455470</td>\n",
       "      <td>37304667</td>\n",
       "      <td>34886838</td>\n",
       "      <td>948215</td>\n",
       "      <td>37708959</td>\n",
       "      <td>38136554</td>\n",
       "      <td>4513492</td>\n",
       "      <td>16939044</td>\n",
       "      <td>12170630</td>\n",
       "      <td>18937918</td>\n",
       "      <td>8896205</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       device_model device_type device_conn_type       C14       C15  \\\n",
       "count      40428967    40428967         40428967  40428967  40428967   \n",
       "unique         8251           5                4      2626         8   \n",
       "top        8a4875bd           1                0      4687       320   \n",
       "freq        2455470    37304667         34886838    948215  37708959   \n",
       "\n",
       "             C16       C17       C18       C19       C20       C21  \n",
       "count   40428967  40428967  40428967  40428967  40428967  40428967  \n",
       "unique         9       435         4        68       172        60  \n",
       "top           50      1722         0        35        -1        23  \n",
       "freq    38136554   4513492  16939044  12170630  18937918   8896205  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_X[column_list[11:23]].astype(str).describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The unblance ratio of the positive and negative samples are 0.169806\n"
     ]
    }
   ],
   "source": [
    "#计算一下正样本和负样本的不平衡性\n",
    "a = train_Y.astype(str).describe()\n",
    "unblance_artio = (a['count'] - a['freq'])/a['count']\n",
    "print(\"The unblance ratio of the positive and negative samples are %f\" % unblance_artio)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The number of NULLs in each characterstic:\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "hour                0\n",
       "C1                  0\n",
       "banner_pos          0\n",
       "site_id             0\n",
       "site_domain         0\n",
       "site_category       0\n",
       "app_id              0\n",
       "app_domain          0\n",
       "app_category        0\n",
       "device_id           0\n",
       "device_ip           0\n",
       "device_model        0\n",
       "device_type         0\n",
       "device_conn_type    0\n",
       "C14                 0\n",
       "C15                 0\n",
       "C16                 0\n",
       "C17                 0\n",
       "C18                 0\n",
       "C19                 0\n",
       "C20                 0\n",
       "C21                 0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"The number of NULLs in each characterstic:\")\n",
    "train_X.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x=train_Y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x=\"hour\",data=train_X)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x=\"C1\",data=train_X)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x=\"banner_pos\",data=train_X)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    29109590\n",
       "1    11247282\n",
       "7       43577\n",
       "2       13001\n",
       "4        7704\n",
       "5        5778\n",
       "3        2035\n",
       "Name: banner_pos, dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_X['banner_pos'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50e219e0    16537234\n",
       "f028772b    12657073\n",
       "28905ebd     7377208\n",
       "3e814130     3050306\n",
       "f66779e6      252451\n",
       "75fa27f6      160985\n",
       "335d28a8      136463\n",
       "76b2941d      104754\n",
       "c0dd3be3       42090\n",
       "72722551       28216\n",
       "dedf689d       24500\n",
       "70fb0e29       24224\n",
       "0569f928       17106\n",
       "8fd0aea4        7482\n",
       "a818d37a        3230\n",
       "42a36e14        2515\n",
       "e787de0e        1209\n",
       "bcf865d9        1045\n",
       "5378d028         483\n",
       "9ccfa2ea         318\n",
       "c706e647          28\n",
       "da34532e          23\n",
       "74073276          14\n",
       "110ab22d           6\n",
       "6432c423           2\n",
       "a72a0145           2\n",
       "Name: site_category, dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_X['site_category'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "site_id site_domain site_category app_id app_domain app_category device_id device_ip device_model "
     ]
    }
   ],
   "source": [
    "from sklearn import preprocessing\n",
    "feature_list_B = ['site_id','site_domain','site_category','app_id','app_domain','app_category',\\\n",
    "'device_id','device_ip','device_model']\n",
    "# feature_list_B = ['site_id']\n",
    "for each_feature in feature_list_B:\n",
    "    print(each_feature+\" \", end='')\n",
    "    le = preprocessing.LabelEncoder()    \n",
    "    le_data = le.fit_transform(train_X[each_feature].values.ravel())    \n",
    "    train_X[each_feature] = le_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_corr = train_X.corr().abs()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(22, 22)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_corr.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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RmKSE61y/lkxOTg57d/nTo3cXLZmevbuwfYt6RtV3bwAd3NXl5t6lHRdiLhMXo55FzszMJr9glPytEQP447fVgDq+Z2RkIdENsmPwZigVCsVqhUIRq1AoAhQKRQWFQuGiUCjOKBSKaIVCsUehUFQFUCgUxxQKhWvB/xYKhSKp4P/3FQrFDoVC4QME/GM50dOH/MJfsExJScPWxkpLxMbWihvJ6u1u8/LyyM6+h7l5VWxtrEhOTtVKa2OrTiuEwN9vC2fP+DN61AiNTJ3aNWnfviWr1yygUeN6NG/RRJPW2sZS266NJckphXbv3buPuXlVLZn+/XsRHRXLs2fPtM4PGdqXXTt9sbGxJCW5cEeulJT0Ynasbaw0Mnl5edzLvo9ZgZ0Wrk05E+LPqbN+TJowg7y8PJyc7LlzJ4NlK+YTdHIfi5fMxdi4gpZOWxtrkm9o27WxtS4iY0XyC3az790rlr+SsLEpLA+17hLK7IWyKc13JeHrs4nkGxHcf/CQy1cSyi0PL8PK2pK0lJuaz2mpN7Gyrl5MJjX1psbu/XsPqGpWBb99h3j06BEhcYGcjgpg1dL1ZGcVdtrKoz4AIATee9dxPGgv73/wltqWrXY5JaekYfOabatoGSe/0Lb09PTYuHEp7h3bEBh4gnMhEWWmuyjPddQuaLcffvA248Z+gGuLpq+0U1p8qFnTkTt37vLnmt8IOXeQlSt+oUYNB5KTUzXxoSzsqIvl5XFoycp5NGhYF5fmjQFITbmJtbV2fbCytiQl5YX6cO8+Zmbq+uDgaMeRoD3s3b+R1m1a8J9gbmXO7dQ7ms930u5gbmleqrzHMA/CjoaWet3mhTYJBfHB9s3jw4ABvYkqElttbKy4desOvXt348jR4DKt06EhAaSlRGvq9Iso9ZV0HdiV0GOhmFtZcDu1sNN1J+0OFlal++tFEi4k4tbJFUMjQ0yqmtC0TROq2RQuy9JVbL1yNVFTpwBSU9KL1TtrG0tSktML7WQ/wMy8KsbGFZgw6WPm/7S4mA09PT2On9zHpYQzHDt6krDQKK3n6PM8ldWzduWKXzh9xo8vv/qsoJ2ka66lpaaXHLdTXsjTvfuYmVWhlrMjAsGWXasIOL6TcZ+rl4+amKoHOL+c/hkBx3eyat1vWFR7vbLWKf/SpUSyY/Bm1AaWCiEaAlnAIGAD8KUQoglwHvVWUa+iDfCeEKJL0QsKheJjhUIRqlAoQtds2FKGt/5qio6EKhTFfzBPiNLOq9O6d+pPy1Y98fQaydix79O+vXpEV6mvpGoVU2bN/IXQ0Cg2blxaql1eoh+gfv3a/DDnKz777JticoMHe7F9x75S7/0VZjR2wkKjaO3Wi87uA5g85RMMDQ3Q19enqUtD/lyzmQ7t+vLw0eNia21fprNQ5uX5K43XSfc69kvC02skjk6uGBoY0KhRvdew85/l4aW8lu9KlnFp3oj8vHxaNuxG++a9+OjT97B3tH0hXdnXBwCPbkPp2L4fgwZ+yOiPR9KhfavXLKc3b1v5+fl89fUctm7bi5trMxo2rFtmuovyXFa/oN3+MGchp06F8PffK/5jO/pKJc2aNWblyg24tezBw4eP6Ne/F1AYH8rCDrw6Ds2d/RvhYdGsWbeoVF+Upv9m+i2aNexMlw4DmDH9Z1asWUClyhWLyb6S16iTz+k0oDPOTWqza+WuN1H3xu22fv3azJnzFePHf60lo1Tq4e7elmXL1pKYeP0NdL+6Tru6eeBYw1WrTj/nsx8/JeZsDDHnYkvJX/FzJRF+IpyQo6H85r2Ar5d8yYXwi+TlFu5Br6vY2qBI/kq2U/K9fDX9c5YvWauZHXiR/Px83Nv1pVG9DjRv0YT69Wu/Xnv/D561H344gZYte9K92xDatXWjbXu34jqKfC7tXpRKfVq2bs6nH02jX8+R9PLsRvuOrdFXKrG1sybkbAQe7oMJC4lk5pwviumQlA+yY/BmJAohIgv+DwNqAVWEEMcLzq0Hir/VVJxDQoiMki4IIVYJIVyFEK6j333pLlT/Hfm56lmDAmxtrUlNu6klkpKchr2d+iUhpVKJqakJGRmZJKekYWdno5U2rWAUN61Ax+3bd/He64+bm4tG1x5vf1JS0jEyNCQ/Px8LCzNsba01U5bPSU1Jx8620K6JSWXNNKKNrRVbtq7ko9GTNQ+o5zRuXB99fSWRETGkpKRja1c4ym1ra0V6kfylviCjVCoxMa1MZpHpysuX4nn46DENGtQlJSWNlJR0wkKjANjr7Y9Ls8Za8skpadjZa9tNS00vLvOCXVMTk9eaJk1JKSwPte4SyiwlXVM2RX33Kp4+fYrv/kPUq1e73PLwMtJTb2JtWziiZW1jyc107WUZaak3sSkY9VIqlVQ2qURWZjb9Bvfm2JGT5ObmcvdOBmFnI2ji0lCTrjzqA6BZGnXn9l18fQJwc3PRajcAdrbWmnahuZ9S2lbRMrZ7oW09T2dZ3YLjJ07Rw6NTmeouScfzdmtra01kVIym3b7MTmnxITkljeTkNM2o8K7d+7G2qo5dGduBV8eh1JR0jIzUccjcvCo2tpbFlrmlpaZja/tCfTCpTGZmFs+e5ZBZsOwqOjKWpMTr1HKuUaIfX8bdtDtUsylcGmRhbUHGrbvF5Jq2d2HY+GH8MGo2uc9yi11/jrrtv1jHrTWza4UyaaXGB1tbK7ZtW8XoEmLr228PJD8/nyVL/gLKtk4DZGff09Tp54yYOBxTc1NWzl4FqGcIXhzlt7C24O7N4v4qjS2LtzKu53i+HjEdhQJSErVH03URW+vUrampU6B+nhWtd+o4ZFVox7QSmRlZtHBtyqwfphEZc5RPxr3PpCmfMPrjkVpp72Xf52TQWbp276i+X1vtPJXFs/Z52T148JDt2/dRrbqF1syUtY0VN9OKt6Xns0SFbSmbtNR0Tp8MISMji8ePn3Dk0AkaN21ARkYWjx4+ws/nMKBeyte4SYPX8rVOEfnlf/wDyI7Bm/HiIsI8oMpLZHMp9K9RkWsPy/Km/hNE7lMUShXo6aNSqRg2tB++vtorm3x9A3jnHfXOD4MG9eHosZOa88OG9sPAwAAnJ3ucnWtwLiQCY+MKVKqkHjkzNq5A927uxMaq1w7u23eQzp3bERYWRb36zlSoYER29n0GD/Zi//5DWnb3+x1ixMhBgHpa+/jxU4B6R5Pdu9Yy87v5nDkTVixPQ4b0ZccOHwDCw6KpVcsJR0c7VCoVAwd74ucXqCXv5xfI8BEDAeg/oBcnjp8GwNHRDqVSvQuGvb0NtWvX4Nr1ZG7dukNKShrOtdVfAtw7teVCkbWeoaFRODvXwMnJHpVKxdCh/fD11c6fr++hQr8O7MOxAr++CrVup0LdQ/qWrHvkYAAGvobuihWNsbJST/sqlUp69uhCcPDZcsvDy4iKiKVGTUfsHWxRqfTxGtCTQ/7HtGQOHzjGoLf6AtC7b3dOBZ0D1F9K2nZoCUAF4wo0c21C/JVETbryqA9F63uXLh2Ijb1ESGhkMf/5FGlbPqW0LR/fAIaW0LYsLMwwNTUhJDSS2rVr0rtXN+Ljk8pEd0k8z0PwyXN07dqBYUP7cT46DgMDA+7cUY9pvGl8uHnztnrZUJ1agHrnkzNnwnB2rsHJMrTzOnEoIvw8deo6U8HIiHv3HtB/YB8O+BWuawc44HeEYcMHAODVvwfBJ84AYG5eFT09dWh3dLKjZi0nriXdKNGPL+Ny1GVsathiaW+Jvkqfjl4dOXvorJZMzYY1Gf/TeH4YNZvsu9kv1fc89jg6quvdkCElxNb9hxkxQh1bBw4sElt3r+W77+Zz+rT2cqWZM6eSk5NDXl6eRndZ1mkAIyMjunbpwKVL8QB8+MHbuLq34Kfx8zQj2JeiLmPrZKPxV6e+7pw5dOa1fK2np0flKurlKTXqOVGjfg3CThQ+Q3QVW0+fDKFmLSccnsehQX04sF87Dvn7BfLWcHUc6te/J0HH1Xns02M4Lo0649KoMyuWreO3BStYs2oT5hZmmqU3RkaGuHduy+XLCYSFRVHLuTDmlcWzVqlUapYa6evr07NXF04FnaVGLUfsHW1RqVT0G9SLg/5Htewc9D/K0Lf7A+DZz4PgE+p6fizwJA0a1qVCBSOUSiWt27lx+dJVAAIOHNPE9PburblcUDckOuCffqv7/8pBkV2JgKnALCAK6FBwbhbwW8H/a4CxBf9PBJIK/n8fWPI6Nt90V6IJ4z4Sbdu0Eg3q1xcd2rURW/5a9lL5nKxUkZ/7VFy9mii+nfGz0FfZiB/mLBT9B7wn9FU2omKlGmLHTh9x5UqCOHcuXNSu01qzu8e3M34WV68miouXroo+niOEvspG1K7TWkRFxYqoqFgRE3tRo/P5DiSbN+8UsTEXxdWriSL5RqqIj08SM2fOF8YVHMXcuYvE4MGjhHEFR1G1Sh2xa5evuHo1UYSERIgG9dsL4wqOYtasX8SDBw81NqKiYoWjQ3PN7ggJCdeES9MuwriCozCpWFMMGvChuHI5QSTEJ4nZs34VJhVrip9/+kMMG/KRMKlYU1Qzqyf27N4v4q8midCQSNGkobswqVhTfDRqsoiLuySiomJFZMR58fawMZpdZ9q17iPCw6LF+fMXhM++AFGteoNiuwd59X1HXL4cL67GJ4oZM34WKgNbMWfOb2LAwPeFysBWVKpcU+zc6SOuXE0U585FiDp122jSJiZeF3fvZor79x+IGzdStXYDMjC0E30LdMfHJ4kZ380TBoZ2Ys6Pv4mBAz8QBoZ2orJJLbFzp4+4WqC7br22ml0xEpOK6G7aWdjZu4iQkEgRHR0nYmMviqVL/xJGFRzKJQ+//rpM3LiRKvLy8sSNG6li9uwFWjsOOZg1Fu8NHSvirySKpITrYv6cP4SDWWOxaP5y8eHwz4SDWWNR27qF8PU+KBLjr4mIsGjRrllP4WDWWNSzbyl8vQ+KSxeuiMsXr4ofv9PWXR71oUlDdxEdHSeio+NEXNwlMXvWr5odWjy9RopLl+M1bUtZ0Lb6DXhPKFU2wrhI23Ku01qTtmjbUqpshEvzriI84ryIio4ViUnXxZ07d8tMt1JlI7Zs3SNSU9PFs2fPxI0bqWL0R5OFp9dIcflyvLh3775IT78lwsOjxcaNO/7j+KCvshEtXLuL0NBIER0dK7z3+guLavXL3M7rxKG42EsiIT5JpCSniYSEa+LH2QuFhUkd8cvPS8SIYZ8IC5M6wrZaI7F3j79IiE8SYaFRokWTLsLCpI54f+R4cSHusjgffUFERcaI4UPHaHYl+mPRapGSnCby8vJESnKa2Lxw00t3Jpr57nciOT5ZpCalivXz1os+9r3F37/9Lb7/8HvRx763iAiKEBm3MkR8TLyIj4kXZwLOlKrLyMhB9Ov3niY+fPfdfGFk5CB+/HGRGDToQ2Fk5CBMTWtrxdZ69doJIyMHMXOmOrZGRsZoDnv7ZqJWrZZCCCEuXLgi4uOTxJMnT8StW7fLvE6fj7kgZs6ar5HPyckRKUmp4mrMVXE15qpY/8sG4WHXU0x/Z4a4EX9DpCSlirXz1gkPu55i02+bxXcfzBQedj3F+D6fi1upt8Xjh49Fdka2SLqYJDzseoo+tbxE0qVrIunSNREXdkF84jFOazcjXcVWC9O6YsjAUeLKlQSREH9N/DBrgahayVnM/2mxeHvox6JqJWdhZd5AeO/208Qhl0adtXYlqlrJWfz84++aXYnateojoiJjRcz5CyIu9pKY+8MiUbWSszCu4CgG9C+sD2XxrLUwryfCw6PF+eg4ERt7SSxd8pewqdpQDB88Rly9kigSE66Jn2YvElam9cWCeUvFu2+NE1am9YVj9aZi354DIiH+mggPjRItm3TX7Fj06UfTxMW4K+JC7GWxZNEazXnXRl3F6ZMhIjbmojhx7LRo0bCL+Ke/BxY9niaFifI+/ol8KQq+rEpegUKhcAJ8hRCNCj5PBSoB3sAKwBhIAD4QQmQqFIp6wHbgAXAEGCmEcFIoFO8DrkKI8a+ymXMnQSeFY2zTQRdmADDQV+nEjr6eUid2HueUvINQeVDSOs3yQJcxwbqSmU7sZD3VzSTdw2dPdGJHl+im1umWKhUq6cROK1NnndgBCLwIqeIdAAAgAElEQVQdoxM7OXmlL2cqS7paNtGJHYBjOvJdRVXRxQPlx9O8HJ3YMTEw1okdgLSsuP+pcPTsWni5PywNHJvrPM9lul3mvxkhRBLQ6IXPv75wuXUJ8heBFyPbtwXn1wHryuMeJRKJRCKRSCQ64B96B6C8ke8YSCQSiUQikUgkEjljIJFIJBKJRCKRvBH/0O8MlDdyxkAikUgkEolEIpHIGQOJRCKRSCQSieRNEPIdA4lEIpFIJBKJRPJvRc4Y/A+jq21EH6UG6cQOwDTXb14tVAYs1lGeGpg56MQOQNL9kn+ltqzpYdH41UJlxJ600FcLlQEOJtV1Ykep0N1Yy72nj3Rix15HvovbO1UndgAGv/23TuyEZOvuR5lqm9q8WqgMuP3k5T+0VlZE37+mEzsAxvqGOrGjqzYLYKzSTZ4e5epuy+7/OeQ7BhKJRCKRSCQSieTfipwxkEgkEolEIpFI3gT5joFEIpFIJBKJRCL5tyJnDCQSiUQikUgkkjchP++fvoNyQc4YSCQSiUQikUgkEjljIJFIJBKJRCKRvBH/0ncMZMdAIpFIJBKJRCJ5E+R2pRId0hO4dCEumC+++LTYRQMDAzZvXs6FuGBOBvvg6GinuTZt2nguxAUTE3OC7t3dNeevXD5DRPhhQkMCOHPaT0ufnpEJ+lXs0K9ih56x2Stv7tu5C+nY5y36j/zkP89hAfXcm/J14EK+ObaIrmP7FrvuPqo3Xx76lS/85zF287dUtbXQXPP8ajjTDv7CtIO/4OLZRkvfxbhgppXiu783L+diXDCnivjuy2njuRgXTGzMCTxe8N3qVQtITY4iMiJQS1fTpg3ZtH812w+vZ8vBv2jUrAEA7Tq3Zl/wVnxP7+DD8e8Uu4cWrV3YFrCO8OQgunt21pyv27A2G31Xsfv4ZnYe2UiPfl2Lpe3WvSNhEYeJjD7CpCnF/W9gYMDa9X8QGX2EI8d24+Bgq7bZognBp30JPu3LyTP78fTy0Eqnp6dH0Ckftu9cU0yni3szfj+yjMXHV9B/7KBi1z1H9+W3w0v49cDvfPf3bCxsqwHg1KAGP+6Zx8JDi/n1wO+09WxfTGdZlZOhoSGnT/oSFnqIqMgjzPxuika+S+f27DvyN0dD9hF34zRBEX588vkHJdhU8ceanzlybi+7D27A1t4aAH19fX5ZMhv/E9sJOLWLsRM+BKCGsyO+R7dqjqjEID4Z9z5du3XgbPhBQiMPM2HyxyXm7c91iwiNPMyhIzuxLyij59jaWXM9LZLxn4/SnPPq14PrqZGk343jUsIZ3Fq6/Ff+Aujh0YnYmBPFymDVyl8JCz1EeNghtm1dhXHFCnTs0paIq8e5mHKW0zEBBJ71JjL+RJn6Tmldt5ivTp6/St+vl+L51WL+3B9c7Hra3WxGzV/P0FmrGPzdCoKirwCQk5vHjD/3MmjGCoZ8t5KQi0nF0pZGc/cWrDi6klUnVjN43JBi1/uP7s+ywOUsPriEH7f8SLWC+l4anbu252SoP2ciDvLZpI+KXTcwULFq7ULORBzEP3Cbpj7YO9iSlB5JYNAeAoP2MP+3WZo0u303cDLUX3PNwqJ43C7PONS5a3uCQvZzKvwA4yeOLjFPK/5awKnwA+w/vBU7h8LfWKjfsA4+AX9z7PQ+jpz0xtDQAIC/d67kcPBujp3ex7yFM9HT0ys3W89Zt2UJR0/tBaBrt46cCw8gLCqQiZPHlGDHgD/X/05YVCCHjhZvt3Z21txIj9Jqt4uX/cTlxLNExR7jXHhAmcU7OzsbDgfs4Hz0MaIij/DZ+EKbf29eTmhIAMGnfbmScJbbGRfK9HlxPu4Ep8/5E3zal2NBhb4LDT9ERNQRJpXiu7Xr/yAi6giBR3dp7DRv0YSgUz4EnfIh+LSvlh1T08ps2LSEkPAAzoUdxK1ls2J6JeWD7BiUAwqFwkqhUGxVKBTxCoUiTqFQ+CkUijoKheKAQqHIUigUvi9JrgSWAr2aNO3MW8P6U79+bS2BDz94m6zMbOo3aM/vf6xm7tzpANSvX5thQ/vR1KULnp4jWPzHXE1wBejWfQiubh60btNbc87dvS0KA2Nys5LJzUom/3HWK/PXv3d3Viyc8yYuKRGFnoJBsz9k1fs/M6/7FJr1bYels3awTYlLYqHXN/zS60ui/M/i9fUIABp0boZdQyd+7f0li/p/S5ePPTEyMdboa9y0M8NK8V1mZjb1GrRn0R+r+ekF3w0d2o8mLl3oU8R3GzZsp4/niGL3//Pc6axY8CdDu73H0vmrmTTjU/T09PjmpymMHT6Z/h3fpteA7tSs46SVLi0lnW8n/ID/nkNa5588fsL0z2Yz0H0EY9+exLTZE6lsUklzXU9PjwULv2fQgA9wa9GDwUO8qFvPWUvHu+8NJSvrHi5NurB0yV98/8OXAMTFXca9fT/at/FkYP/3+X3xHJRKpSbd2E8/4PKl4j/GpKenx6gfxvDje98zqdt42vXtgF1tey2ZxNhEvvSczNSeEzjjd4p3vn4fgKePn7J40iImd/+MH9/9nvdnjsLYpKKWzrIqp6dPn9LNYygtXLvTwtWDHh6daNWyOQBLlvzElLEzAFi+6C/OnArFa2BPnOvU1LI5dER/7mXdp0vLfvy1YjNfzpwAQO9+3TAwNKBXx6H07TqCt98bhK29NYlXr+HZ+S08O79F367DefLoCX77DzN/wSyGDhxNG7deDBrsSd262mU08t3BZGXdw9WlG8uXrmXW7C+0rs/9eTqBhwq/dOvp6bFk+c8s/HUZ9lZNuXXzNnlFRqre1F96enr88fuPeHqNLFYGU6bOooVrd5q36M6N6ym8N/ptvp/3FX27DqexUzsy7mTit/cQB30LO8pl4bu8jGStPOXl5zN3kz/LJg1nz5xxHDgbS3zKbS2Z1T5B9HBryPZZHzNvzCDmblQPeuw6Hq7++8MnrJg6kgXbDpGfL3gVenp6jJ0zlpnvzWRc17G49+2IfZH6Hh+bwKQ+E/msx3iC95/kg28+fKm+nxd8x/DBH9GhpScDBvWhTt1aWjLDC+pD62Y9WLlsPTO+L+zUXku8TtcOA+jaYQDTJs3SSjfuoy801+7cyShmtzzj0Nxfv2XE4DG4t/Ki/+DexfL09juDyM66R9vmPVm1bD3fzlLnSalUsmTVPL6c/D2d2vRlkOd75OTkAvDxB5Pp1n4gndr0xdyiKl79e5SbLYDeXt14+OCRJk+/LJzFkIGjaO3ak0FDPIvF1nfeG0J2VjYtmnZVt9sfpmld/3HedA6/0G4BtmzezdCBo7Gyrs6QgaPKLN7l5ubyxbTvadykE+3aezF27PsancNHjMXVzYOO7fpiZGTImlWby/x50afXcNq38aRTh34Fz6VZDB74IS1dezCoRDtDyMrKplnTLixbulZj50LcZTp16E+Htl4M6v8Bi/4otPPz/O84fOgEbs09aNfak8uXrvI/h8gv/+MfQHYMyhiFQqEA9gDHhBC1hBANgG8AS+AXoPjQjTYtgatAQk5ODtu278XLq4eWgJeXBxs37gBg1679dOncvuB8D7Zt38uzZ89ISrpBfHwSLd1e3sseM+Zd8h+/8EuWr1ERXV0aY2pS+ZVyr8LBxZk719K5e+MWeTl5RPicopGHq5bM1dNx5Dx5BsC1iCtUsVKPjFnWtiX+7AXy8/J59vgpKReu0+HdHhp9OTk5bN++l75FfNe3FN/19erB9lJ8FxR8lozM4h0mIQQVK1cEoHLlStxOv0OjZg24nphMyvVUcnNyOeB9mM49OmqlS72RzpUL8eQX+XJ3LeEG1xPVX45u37xDxp1MqppX0Vx3dW1KQsI1kpJukJOTw66dvvTx7K6lo49nN7Zs3gWA9x5/OnVqC8Djx0/Iy1PvoGBkaIh44TuSjY0VPXp2Zv26bcXy6OxSm/SkdG7duEluTi4nfYJw7d5SSyb29HmeFZTR5YhLmFmbA5CWmEp6UhoAmbcyyL6TjYmZiZbOsiynhw/VD3mVSh99lQpRkEkhBM1cG3Mt8Qa5uXncTL2F756DdO/VSctmt16d2LXVBwD/fYdp26FlQXowNjZCqVRiZGRITk4OD+4/1ErbtmNLriUlY2lpQWLCNa4VlNHuXfvp5ak94tq7Tze2/r0bgL3eB+jYqU3hNc9uJCXd4OKFK5pzHTq2Rl9fyaKFqzTl3tG9jZbON/VXS7dmxMcnkZh4vVgZ3L//QKPXqIIRVjbVuZZ4gxvXUsjJycV3z0H6D+mDz+4DZeo7nmqfj0lIwb56VeyqV0Wlr6Rnq4Yci7ykJYMCHjxW//Lqg8dPqFZFHZcSUm/TqkENAMxNKlLZ2JDYpFReRR2XOqQlpXLzejq5Obmc8DlBa4/WWjLnT0fz9Ina5qWIi1hYW5SkClCPiCYmXOdaUjI5OTl47/ajZx/t+tCzd1e2/+0NgI/3QdoXKdv/hPKMQ81aNCYp4TrXr6nztHeXPz16dymSpy5s36LOk+/eADq4q33o3qUdF2IuExejLsfMzGyN/ef1Ql9fH5WBuv2Wly3jisaMGfcev/+6EoAWBbFV02537qd3n25adnr16caWzXsA2LvnAO5F2u21RO12C3DqZAi2dtY8e5aj0V0W8S49/RYRkTFqvz14yMWLV7C1sdLS6eraFENDA9as3lSmz4uitCjyXNq905c+RXzXu083/t68W2Pnue+07BgZamJ25cqVaNfOjQ3rtwOQk5NDdvb90m9CUqbIjkHZ0xnIEUKseH5CCBEphAgSQgQCr6rdtsCN5x9SUtKKNXgbWytuJKsfcnl5eWRn38PcvCq2NlYkJxc+/FJS0rCxtXp+D/j7beHsGX9Gjyoc/a5TuyYKlRFKUxuUptYodPTT8ABVLM3ISr2r+ZydloGpZelLmVoN7cyFY5EApF64Tv1OLqiMDKhYtTK12zTAwslKS19ySho2r+k7G5vC85q0ttppizJ56kwmzxhPQJg3k2d+xu9zl2NpXY2bqbc0MjfTblHd+uVLDUqiUbMGqFQqbiSlaM5Z21iRnJym+ZyakoaNtaVWOmsbS41MXl4e9+7dx8y8KqB+UJwNOcDpc/5M/PxbTUD+ef4Mvpv+c7EvCABmVubcTbuj+ZyRdhdzK/NS77vrsO5EHAsrdt65aW30DfS5eS29mM6yKic9PT1CQwJIS4kmMPAE50IiABgzZirfzpmKa6tm9B/ahxW/ryUt9SaWRcrF0ro6aSnpGpv37z2gqlkV/Pcd5tGjJ5yJPURwpD+rl24gO+ueVlqvAT3w2X0Aa2srUlJeLKN0rEsoo5TkQjv3sh9gZl4VY+MKTJj0MfN/Wqwl36hJfR4+eMSSFfM4FryXLl074GCvPbP2pv56Ub6kMlizeiEpNyKpV9eZsHNRpKXe1Fx78uQpVc2rcCoopEx9V5RbWfexMjPVfK5e1YSbmdrhc2w/d/afPk/3Kb/x6aItfDWiJwB17C05FnGJ3Lx8km9nciEpjZsZ2nZLwtzKnNuphXXzTtodzC1Lr+8ewzwIOxpa6nUrG0tSi9QHq6L1wbq6ps6ofXcfMzP1F3EHRzsOB+1mz/6NtGrTQivd70vnEhi0h0lfjC1mtzzjkJW1JSkFZQ2QlpqOlXV1rXRW1pakvlAf7hXkqZazIwLBll2rCDi+k3Gfa8+2bNm1ivNXg3hw/yG+ewPKzdaX0z9jxdJ1PHr8GHjeJou0WxvtcrJ5QaZ4ux3DvCLt9jmWlhbkvjBTUdbPJUdHO1yaNuLsuQit8526tOPBg0fExycV5KlsnhdCCLz3red48F7e/+AtLb8ApJTgO2sbqyK+K7TTwrUpZ0L8OXXWj0kTZpCXl4eTkz137mSwbMV8gk7uY/GSuRgbVyjRv/8o+fnlf/wDyI5B2dMIKP7N6DVZuHBh923btvVTKBSh+fnqERRRpLuunpTQRojSzqvTunfqT8tWPfH0GsnYse/Tvn0rAJT6SlDokZedSv7DDJSVqxfTUW4Uv11KG5po0b899k1qcmSVelTyUlA0cUcjmLB7Nu/88RlJ4VeK+Umt7r/3XWmM+fhdfpn5Ox4t+vPLzN/5fuE38B/oKYpFdXPmLv6O7ybO0Upbguri+SvJqQUyoaFRtHLrSaeO/ZkydSyGhgb07NmFO7fvElkw+vQ6lJafDgPcqdnYmX0r92idr1K9Kp/9NollU/8oNW1ZlFN+fj6ubh441nDFzbUZDRuq16xPmPARyxf9hc+eA+zcspfpc6Zo9L3apqBp84bk5+XRppEH7i36MHrcO9g7Fn4xV6n06drTHf99h16vjEqx89X0z1m+ZK1m5uM5+kolZuZVWbvmbzq178ezp89o4tLwNXSWbutV9X30R5Oxd2zOhYtXaNGyqZbc89mXFzuSZeG7ku6/KEXN+J+NoW+7phxaMImlE99m+mpv8vMF/Ts0w7KqCcNnr+aXLQdp6myPUvkaj7tS/FgSnQZ0xrlJbXat3PUm6kqqeCWK3Ey/RfOGXejWYSAzp//M8jW/UqlghnLcR1Pp1LYvfXuNpHVbV4a81e81dJZVHCpBd5HPpdUHpVKflq2b8+lH0+jXcyS9PLvRvmPhjMzbgz7Gpa47hoYGtO/YqlxsNWxcD6eaDvi/sBTuteJ/qe12AsuXFm+3r0r36jy8+r4qVjRm+7bVTJ46U2umD6BNGzcSE6+/3O4bPi8APLoOoWO7vgwa8CEfjXmn2LKhF1S8kL+SzKiFwkKjaO3Wi87uA5g85RMMDQ3Q19enqUtD/lyzmQ7t+vLw0eMS35GQlA+yY/A/xuTJk9cNGzYsXAjhqqdXEVtba1LTbmrJpCSnYW+nfsFKqVRiampCRkYmySlp2NkVvnhla2utGelLK9Bx+/ZdvPf64+bmotElnhV0QHLV0+ModFMtstIzqGJTOBpnam1G9q3MYnJ12jWi+/gB/Dn6F/KeFY68HF7qza+9v2LFO3NBoSDt4nUtfXa21pp8P6c036WkFJ7XpE3VTluUd98ZwuH9xwAI2BdIo2YNuJl6C0ubws6VpXV1bqffKUVDcSpWMmbppgUsnreK6PBYrWupKenY2VlrPtvYWpOWfktbJrVQRqlUYmJSmYwM7WVQly/F8/DhIxo0qEurNi3o1acr5+NOsHb9H3R0b8NniyZpZDPS72L+wlIJM2tzMm5qr2cGaNyuKQPHD2He6B/JfaGMKlSqwNdrZ7Dl101cibhcos6yLqfs7HscP3GKHh6dsLAwo0njBpw5GYq1jSX79wTQ3K0p1jaW3ErXXq+ennoT64LROKVSSWWTSmRlZtN3UC+OB54iNzeXu3cyCTsbSWOXBpp07t3aExt9kTu3M0hNTcfW9sUysiK9aBmlpGNrV2jHxLQSmRlZtHBtyqwfphEZc5RPxr3PpCmfMPrjkVyIu8zTp88IC40C4Pr1FCpXrqSl80399aJ8aWWQn5/Pjh37qN+ojtYIoFvrZoSfiypz3xXFsmpl0jMKlzneyrxH9SraSxj3BEXSo6VaX1Nne57m5JL54BH6Sj2+eLsH278fw++fv8X9R09wqP7qjRXupt2hmk1h3bSwtiDj1t1ick3buzBs/DB+GDVbq74XJS3lJjavqA9pqTc1dUbtu8pkZmbx7FkOmQVLGKMjY0lKvEEtZ/XyqPQ0tY6HDx6ye4cvzVo00dJZnnEoLTUd2xdGra1trLiZVjRP6ZqR7edxKDMzm7TUdE6fDCEjI4vHj59w5NAJGjdtoJX26dNnHPQ/So/eXcrFVgu3pjRp2pBz0YfY67+Jms5OTJryCbZ2RcopraR2+0JsLWi3rm5N+f6HaUTFHmPsuPeZPHUsH40pXDF8M/02+qrCDSDLKt7p6+uzY9tqtmzZg7e3v5Y+pVJJs+aNNUve1Hn6758XgKb+3rl9F999AViYm2v5ztbWivQi+Svuu8pklmTn0WMaNKhLSkoaKSnpmpi319ufpk21B0P+FxAir9yPfwLZMSh7YoEWr5QqnRCgNlBDpVIxbGg/fH0DtAR8fQN45x31bhmDBvXh6LGTmvPDhvbDwMAAJyd7nJ1rcC4kAmPjClSqpB5pMjauQPdu7sTGqtdd7tt3EIWqYIpOTwUodPbCy42oeKo5WWFmVw2lSkkzr7bEHtKebLFt6MSQuR+xZvQvPLhbuBRAoafAuIr6y5F1PQds6jlwcmOARp9KpWLo0H74FPGdTym+8/ENYGgJvnsZqWk3cW2rXt/eqr0r1xNuEBt5Acea9tg6WKOv0qdn/24cCwh6LX/oq/RZtHYePjv8OeRzpNj1sLBoatZywtHRDpVKxaDBnvjtP6wl47c/kLdHqHcO6j+gF8ePnwbU083PX+qyt7ehdp2aXLuezPczf6F+nXY0btCRD977nBPHT7N44m8afVejrmBdw5rq9tXRV+nTzqsDoYfOadl0aliDj38ay7xRP3LvbuEXOX2VPl+s+prju45yxu9UiTrLqpwsLMwwNTUBwMjIiK5dOnDpUjyZmdmYmppw7949nGo64DWwJwlXkvAc0IPDB45p2Qw8cJxBb3kB0KtvN04XLJVJTU6nbQc3ACoYG+Hi2oSEK0madF4De2qWwoSHnadmLSccCspo4KA+HNivvZuVv18gbw0fCEC//j0JOn4GgD49huPSqDMujTqzYtk6fluwgjWrNhF4OAiFAjq6t0GlUtG7T1fOnQ3/r/wVEhqJs3MNnJzsi5VBrVpOGr2efboTGRaDU00H7BxsqF2vFlXNq7JhzdYy911RGtaw5frNDJJvZ5KTm8eBs7G4u9TRkrE2M+FsXCKgfq/gWU4uZpWNefw0h0dP1e+9nI6NR6nUo9Yrdg8CuBx1GZsatljaW6Kv0qejV0fOHjqrJVOzYU3G/zSeH0bNJvuF+l4SEeHnqVnLEQdHW1QqFf0H9uagn3bbPuh3hKHD+6v90b8HwSfU9cHcvKpmAwRHJztq1nLkWtINlEqlZqmRvr4+3Xt24uKFy1o6yzMORYbHUKOWI/YFeeo3qBcH/Y9q58n/KEPfVufJs58HwSfUPjwWeJIGDetSoYL6vZPW7dy4fOkqxhWNqW6p7pAplUq6du/I1SuJ5WJrw1/baFa/Ey2bdKdfr5EkXE2iq/tAatVyLGy3g/vg76fdbg/4BfL2iAEA9BvQkxMF7ba3x9s0bdiJpg07sXzZOhb+upzVKzcWlkXMRQwMVBrdZfVcWr1qARcuXmXR76uKlVG3rh2Ii72ErZ11mT4vin6X6NK1PYcOHafWC8+lgYM98SviOz+/QIaPGKixc6I0O7VrcO16Mrdu3SElJQ3n2uqOsHuntly6+D/48vG/FPk7BmXPEWCuQqH4SAixGkChULgBxkKI46+RPhcYDxw8H32Mdeu3ERd3mZkzpxIWFoWv7yH+WruVdev+4EJcMJmZWYwYOQ5Q7ySwY6cP0VFHyc3L4/MJ08nPz8fSsho7d/wJqJcObd3qTUDAMQDWrtvK4gXT0a9iBwjyHtwq8aZe5IuZPxMSEU1W1j269h/JuFHvMKjIy1SvQ35ePru+W8uYDd+gp9Tj7PajpF9JpuekIdw4n0Ds4TD6fj0CQ2ND3l82EYDMlDv8+dGvKFX6fLZjFgBPHjxm06Ql5D7L1egbLqZofDdr5lRCX/Dd+nV/cLHAd8Nf8N3OnT6cL+I7gE0bl+LesQ0WFmYkJYTy/exfWbtuK5988gXLf/8Zpb6SZ0+f8f0XP5OXl8fcbxawfMsilEo9vLf4En8pkXHTPiIu8gLHAoJp6FKfRX/9jEmVyrh3b8/YL0Yz0H0EPfp2pXlrF0yrmtB3mHrnqBkT5nApVv1CW15eHl9MmcWevetRKvXYuGEHFy9cYfq3EwkPP4+/XyAb1m9j1ZqFREYfITMzmw/e+xyANm1dmTT5E3Jyc8nPz2fyxO/IuFt8dqakMvrzu1VM3zALPaUeR7cHknzlBsMmDyc++iqhh8/xzjcfYGRcgSnL1Lt03Em9w7zRP9LGsx31WzakcpXKdB6sfmFw6dQ/SIpL1OicLKaXSTlZW1vy159qn+vp6bFzpw/7/dQPwTFjv2DJmvmAgs+njSHjbiZb1u/iyqUEJn41lvORcQQeOM62zd4sXDaHI+f2kp11j88/+gqAjX9tY/4f33MgeCcKhYKdW/ZyMU5dJkYVjGjv3opvJ8/RlNG0qd+z0/svlHpKNm/cycWLV/l6+gQiIs5zwO8ImzbsYMXqXwmNPExmZhajP5jEy8jLy+O76fPYunM1enoKEhOu8+03P/3X9XrCxG/x2/83Sj09TRkoFArW/rmIyiaVUCgUREfH8fPXCzl14hzrdyyjqlkVIkOjy8V3RdFX6vH1yF6MXbhZvTyovQvOttVZuucoDZ1s6NSsLlOGeTB7vQ+bAs6iUMDsUf1QKBRk3H/I2AWb0dNTUL1KZX4c3f+Vdf15fV8xYzmzN/6AnlKPQ9sOcf3ydUZMHsmV81c4d+gsH04fhZGxEV8t/xqA26m3+WHU7FLL7uupP7B1958olXps2bSLSxevMu2bz4iKiOGg/1H+3riTJavmcybiIFmZ2Yz5cDIArdu5Me2bz8jLzSMvP49pk2aRlZmNsXEFtu75E5W+PnpKPYKOnWbTuh1UMzTVslueceibL35ky67VKJV6bN20h8sXr/LFN+OJioglwP8oWzbuYvHKeZwKP0BWZhaffDgVUM/mrVy6Hv8j2xFCEHjoBIEBJ7CoZs76LUsxMDRAqackOOgsG/7aVi62SiunaVO+Z5f3WpRKJZs3qmPr199OIDI8Bn+/QDau386KNQsIiwokMzOLUe9PfGV9WrP2N9p1aIWenh5hUYfJyMxi8eI//+t4166tG++MHEz0+ThCQ9SdjBkzfsb/gLojN3RoP3bu8CE5ObVMnxdOTvZs3qp+fVJfqWTH9n0cCjjG1Cmw23sdSqUemzbu5OKFK3zz7UQiCuxsXL+dVWsWEJP/6JMAACAASURBVBF1hMzMLD58X71rWes2rkyaMoacnFxEfj5TJs3UPJemTfmeNX/+hspARVLiDT4dO43PJxbf7vcf5V/6A2eKN113KHk1CoXCBliEeubgCZAETAT+AuoBlYC7wCghxMHS9KgMbHVSOI9SX28kqSyY5vqNTuws1lGeGpg56MQOQNL9ly9tKit6WDTWiR2APWmlv7hZljiY6ObdmaynD14tVEbce1rKmuYyRle+i9s7VSd2AAa//bdO7IRkF98CuLywrFBVJ3ZuP3n5LMn/RZ7kPtOJnfvPHuvEDoCxSjcbiZT0HkR5kf0gXnfGXoMnkb7l/h3NyMVT53mWMwblgBAiFRhawqUOur4XiUQikUgkEkkZI3/5WCKRSCQSiUQikfxbkTMGEolEIpFIJBLJm/AvfcdAzhhIJBKJRCKRSCQSOWMgkUgkEolEIpG8Efn/zO8MlDeyY/A/jIG+Sid2dLVTEMD80Lk6saN0na4TOy2e6W7SrZmtbnYdeefBq7cxLSuqGFXUiZ0WFXWze1TAk9f/Ben/KzzM0c1OKo69f2Bslf/mJ2Ben9iHyTqxk/X0oU7sgO52h8nW0W5YKj2lTuwAWBrrJrbWqGz1aqEyIuXR6/+g3X+DiYFuYrhEd8iOgUQikUj+cXTVKZBIJJIyQb5jIJFIJBKJRCKRSP6tyBkDiUQikUgkEonkTZC/YyCRSCQSiUQikUj+rcgZA4lEIpFIJBKJ5E34f+ydd1hUR9fAf5cFVOxYqCq22AUVewEVUGliT+wmxhY19h41scQWNZYUo7F3BaVXpQlYAQt2AWVhsdBULLDc749dFpbFkrxq8r7f/p6HR3fmzJx7Zs7MvdPu/R89Y6AdGGjRokWLFi1atGjR8lfQbiXSokWLFi1atGjRokXL/yragcG/HHt7G2LjQrh8JZSZMydqxOvr67N7zxYuXwklNOwEtWubA9CjRxciz3hx7pw/kWe8sLHpCECFCuWJjvFV/SXfv4Tb4pEa+Ta2sWR+yHoWhG6k50RXjXibrxyZG7SO2X6rmbh/EVXNqqvinOcNZU7AWuYErMXKuePftn3RyvV0c/oct+ET/nYehTSysWROyE/MC91A91Ls6faVI7OD1jLDbzXj9y9Us8dp3hfMCljDrIA1WDp3eKcuE9uWOEWsxfnMTzSZ7PJGuVpO7fgidT+GLesCoF+1Aj2OLmTg7R20WTHqnXrKd21DXf9t1AvajuG4QRrxlfvZ0SDmIBYnN2NxcjOVB/VSi9cpX476EXswWqzpV8XpaNuOYxH7cD9zgFGTh2nEt2pvyd6A7UTfP0UPJxvN66xggM/F48xeMa3U/HvYdSXmoj/n4oKYOn2cRry+vh7bd27kXFwQAaeOUqu2mVq8mbkJSamxfDPlS1XYhG9GE3nWh4gYb7b9uR69MurfBLGyacXPp35hc9hvuE0coKHTeawrG4K3sM7/ZxYf+IHqZjUAsGhalxUeq1kftJl1/j/TybmLRtqedt24cCmI2PhTTJ8xvhR79Nm5exOx8acIOX2c2kp7WrdpSUSUFxFRXkRGe+Ps4qBK49q3F9K0eB5l3OBO4lnatmulkeeB/b9yIyGSqEgv6tQxV8XNnTOZGwmRXLsajoN9Uf30crDl2tVwbiREMmf2N6rw7radOXfWn7jYEP7csRGJREL3nl24dO00aRkJxN8IJyTCgxlzJqnV0bad64mJDcAv5LCqjmrVNiNJFkdIhAchER6s2bAUgPIVyqvCQiI8SLgXTe/FwzXKqoFNSyafWsvUsJ/oMlGzLVkP68nEgFVM8F3Jl8cWU6OhQm+9Ls0Z572ciQGrGOe9nLqdmmqk7dajEyFnT3L6vBcTvv1SI15fX4/N29dw+rwXHoH7MKtlCoCuri7rti7DL+IYQdEeTJymnlZHRwfv04fZfmAzAA72tly5HErCtQhmzZpUih599u39hYRrEUSEe6rqztCwCgEBh3ny+AYbNyxTS+PluZfz5wKIvRTMls0r0dHRvJV379mFyPO+RF/yZ/K0saXa9/uf64m+5I9v8CFq1TZVxTVp9hnegQcJi/bi9JmTlCmjr5bW3t6G+PhTXL0axqxZpd+X9u7dwtWrYYSHq9+Xzpzx5vz5AM6c8cbGppMqzcmTuzl71o+LF4PYtGmFyiY7+25cjA0m7vIpps/UvBcUtqe4y6c4Fequak9t2rQkMtqbyGhvzsT4qNqTmZkJ3r77OX8xkLPn/Zk4aTQAXXt0JCD6OMHnTjBu6uhSy2vjHz8SfO4Ex/x3Y1bLBAA9PV1WbVqCd9hhPE8fpF2notfu7jvxOwHRx/E8fQDP0weoWq2KWp6durfHPeIAJ6MOMXqypv+37mDJ/sAdnHsQSk8nW1W4ibkR+wN2cDBoJ0dD9zJgZF+NtKDwgTMX/IiJDWDK9K9LtemvtFsAd+89nLngp4ozrF71g5dd+fIGqjLzPH2AszdCWLh8Zqk2/qMUFHz8v38A7VaifzE6Ojqs3/ADLs7DkUplRER44uMTxI0bd1Qyo0YPJisrm5YtbBk40IVly+cxauRknjzJZODAr5ClPaRp08846bmHhg068OzZczp2cFSljzzjxWX/c2p6BR2BAT98yW/DV5Ale8J0z5VcDbpI+h2pSkaakMR6lwXkvXxNp+H2uMwfxp7JP9O0eyvMm1mwznEuuvp6TD68mOuhcbx69tc/kuTmaM/QAa4sWLbub5Seuj39fhjDtuEryZY94VvPFSSUYs9Gl4XkvXxNx+F2OM0fyr7Jm2jSvRVmzeqy3nEeuvp6TDy8mBuh8W+0R9ARaLNyNKc//5EXaRk4+C5DGnCJnNtSNTnd8mX57KtePL5YVJfyl3lcXnuUKo1qUbmxecms1dHRwWjJJB6MWUie7DEWxzfyLCSG13cfqIk99Q0n/YdfS82i+rSR5J57+we5dHR0mLNyOpM/n0F62iN2+24jPCCSxNvJKhmZNJ3vp61k+ITPS81jwpyxXIqJe2P+q39awsC+Y0iVyggKPY6/bwi3bt5VyQwbOYisrGzaWdnTb4ATS76fzdgxRYOM5T8uICQoXPXb2MSIr8ePoHM7R16+fMX2XRvp7NKV0GOnVDq/WjaeZcOWkCF7wo+e67gQfI6U20Vll3gtkbnOM3j98jUOw3szYv5oNkxey6sXr9g8fSOypDSq1jRktc9PxIXHkpvzXJX3T+uX4uY6CqlUxulwD3x9Q7hZrM2OHKWwp5VlDwYMdOb7ZXMZM2oq1xNuYdvVDblcjpFRDc7E+ODnG4Ioivzy2xrWrf2FLZv/JDTiBGKJG8aXY74gMzObxk27MHiwKz+uXMjQYRNp0qQhgwf3paVVD0xNjQjwO0STZl0B2PTzCno7fkFKShox0b54eQdy48Yd/tyxEYfeQ7h9+x5Ll8zi82H9mDpjHMuWrGPgYFdMTI2YOHaWWh0NHTmQrKwcOrTqhdsAR777fibjxswAIDnxPj279lO73ufPnquFBYYd57r/BTUZQUfAcdlo9g77kRxZBl97LuNm8CUeFWtLV05GcWF/CACN7FrTa9Ew9o1aQ27mUw5+uY6nD7Oo+Zk5w/fOZX37KWp+98OaBYwYMB5Zajongw8Q7B/KnZv3VDKDh/cjOyuH7m1dcO7Xm3lLpjFl7Bwc+9qjr69Pn64DKVuuLEFR7nge90f6IBWAMeOHcefWPSpUrICOjg4//7wcR6ehpKSkEXXGG2/vIG7cuK3SM2b052RlZdG0WVcGDXJlxfIFDB8xiZcvX/H99+to1rQRzZo1UiubocMm8vTpMwAOHfydAQOcCfY6pWbfj+u+Y7DbV6SlpuN/+giBfqfV62zEQLKysunYujd9+zuyaOksxn85A4lEwtZta5g8fi4JV29StWoV8vLy1fLeuHEZTk7DkEplREZ64u0drGbT6NFDyMzMpnlzGwYNcmHFinmMGFF4X/qSNOV9yctrL/Xrtwdg+PBvVDYdPPgb/fo74uHuy0/rv6evy0ikUhmhESfw9Qku0Z4Gk5WVg1VL9faUkHALmy59Fe3JuAZRyvaUL89n4YKVxMddo0KF8oRHenI15ipLV81j9KBJyFLTOR64l1P+Ydy5lajSM3CYGzlZOdi1c8PJzYHZi6cy7ev5DB6h8GNnmyEYVq/KjkOb6W8/AlEUAZg5YRFX468DUFG3nFo5zl05g0lDppOe9pB9ftsJC4wk8VaSSiYtJZ2l365kxMQv1Or/UfoTRrtMIO91HuUMynE0dA9hAZE8Tn+ilv+qnxYz2O1LUqXpBJw+SoDvqf+o3RYy6evZxMcq7h1Vylb84GX3/Hkurt2HqtJ7BO8j0OcUo8cPRcvH51+9YiAIgoUgCP97nxJ9T6ytrbh3N5mkpAfk5eVx7JgXzs4OajLOTg7s33ccAA8PX2xtFTMw8fHXkKU9BCAh4RZlypRBX1991qd+fQtq1KjGvXM31MJrWzXgcbKMJw8eIs+TE+sVRXMHazWZO9EJ5L18DUBy7G2qGBsCYNTQjLtnr1MgL+D1i1dIr9+niY3l37PfqgWVK1X8W2mLU9uqAU+SZWQo7YnziqZZCXvuqtlzh8pvsCf1ejKN32KPYav6PEtK5/n9RxTkybl/MgbzXpofbmo5ZyDXf/FG/uq1Kkz+4hWPz91C/irvnTaVbfkZr5NTyXsgg7x8cnzCqWD3/qszZZo1QLd6FXIjL71VrlmrJjxIkiK9n0Z+Xj5BJ0Ow6aU+S56WIuPO9XuIBaJG+sYtPsOwRlXOhp0vNf/W1i1JvJdMstLHPY770MfJTk2mj1NPDh30AMDzhD9dbTsWi7MjOemB2oMCKGZ1y5Yri0QiwcCgHBnpGaq4BlYNkSXJePggnfy8fM54RWBt304t/bXoK7xW+sOt2JsYmlRT2JqYiiwpDYDMhxlkP86mkmElVbo21pbcu1fUZt2PeeNUwh5HJzsO7HcH4ISHHzZKe168eIlcLgegbNkyqgeLrt06oKsrYcP638nLy+P4US+62ajXtauLA3v3HgXg+HEfenTvogzvxZEjJ3n9+jVJSQ+4ezeJdm1b0a5tK+7eTSIx8T55eXkcOXISV5deVKtWlVevXnH7tuIBOTg4nC+GDyDx3n3SZY8QRZET7r70duqppr+3Y0+OHDgBgNeJALrYvL8v1q1Xh+rVDUku0Q+ZWdUnIymdzAePkOfJueoVQyN79bZUfICuZ1CGQg+UXUvm6cMsAB7eSkG3jB4S/aJ5MMvWzUlOfMCDZCl5efl4efhj38dWLW/7Pt05fsgTAD/PIDp1U/iIKIoYGJRDIpFQtmwZ8l7n80z5QGtsWpPuDl05vE/hr23bWqmX81FPXFzU+3AXFwf27jsGgLu7D927dwYgN/cFUVHnefnqlUaZFT5A6+rqoq+vp/KVQlq1aUnivfvcT04hLy+PE8d96eXYQ02ml2MPjhw8CYD3yQC62ChWQ217dCbh6k0Srt4EIDMzi4JiA9FCmwp9/OhRL5yd7dXydna2Z//+40qbfLG1VdgUH3+NtDfcl4rbpKensMm6RHs6fswbpxK6nJztOKjUdcLDT3UPVGtPZcpQWETpskfEx10D4Nmz59y8eYcOXduSnFTkDz4nAulZwh/s+tjgftgbAH+vEDp2VfhDg0b1iApXTK5lPM4kJ/spLaw0V6hK0rxVE1KSUpDeTyU/L5+Ak8HYltK33r5+V638AfLz8sl7rbhP6JfRQyhlxai10geSk5Q+8IHbbSEtWzf7qGVXp14tqlWvyvno2L98bR8bUZR/9L9/gn/1wODfgiAIn+7b7MUwNTUiRZqq+i2VpmFiavRGGblcTk7OU6pVU/+8u5tbHy7HX+P169dq4YMGu3L8mLeG3ipGhmSlFs08ZKdlUNnI8I3X2X5wd66HKmaEU6/fp4mtFXpl9SlftSINOzalivKh6p+islFVNXuy0p5Q2ajqG+XbD7blRmg8gGIgYGuJXll9DKpWpME77DEwNiS3mK7ctAzKmajrqtq8Dgam1UgN/vsdnZ5RNfJlRZ+8z5c9Rs9I87oqOnTGwnMrppsWoGus3B4lCBjNG8vD1TveqaeGcXXSUx+qfqenPaKGSY33ukZBEJi25Bs2LSt9xQLAxMSI1BSZ6ndqqkzDx01MjJCmKB7GC33c0LAqBgblmDr9a9au2qImL0tLZ+vmHcRdC+Xa7TPk5DzlckTRioWhcTWepBWVXUbaE6oZv7lOew6xJzb0okZ4A8uG6Orrkp5cdP2mpkXXCiCVlmKPqbG6PdlPMVS22TbWlsSc9yPqrC/Tv/0OuVxOy5ZNef4sl19+W0PEGU969uyqsZ3K1MyYBylF/UB2dg7VqlXF1LQoHCBFmoapmbGavCrc1JjHjzPQ09OjTeuWAPTv74SJqRGpUsX1tmlnxagvP2fkmCE0atygyCaTmkilRTY9zXmKoaFi20TtOuYER7jj4bOX9h01B8n9Bjpx0sNPI7ySsSE5aUVtKSctg0rGmu227Uh7poavx37+F/gt2a0R39SxHbJrychfF816G5vUJE1aVG+y1IcYm6jXk5FJTdJSZcVsekZVwyr4eQaTm/uCswnBnIkP4I+tu8nOygFg8Yo5rFq6QfUgV7L8pdI0zEyN1fSYmhqTkvL2Prw0vL32kfIglqfPnuPu7qMWZ2JSk9Ri9qWlpmNiotmuUkups3oNLBCBg8f/IDDsON9M/aqU6y3u42mYmf11m/r1cyS+xH3J03MP9+9f4tmz55zw8MOkhK5UaRqmJe0wNVLJqPoHpS5ra0vOnvcn+pwf06YuUg0UCqld24yWls3IycohTZquCpelpmNUop8zMq6BTCkjl8t5pvSHG1dvYdfHFolEgnltU5pbNsHErOgaV21aiufpA3wzQ307Vw3jGsikRX3rw7RH1DR+v74VwMi0JodDduF70Z3dW/arrRYAGBdrtwCpUpmGj//ddvvz1pWERHgwffZEZVv6OGUH4NKvNz4ngt67XLT85/w3DAx0BUHYLQjCZUEQjgmCYCAIwmJBEM4LgnBVEIRtgiAIAIIghAqCsFoQhHOCINwSBKGrMny0IAjugiD4C4JwWxCENYWZC4LgIAhCtCAIlwRBOCoIQgVleJJSTySguYG7SN9GQRCilNfSThluKAjCCeU1xwiC0FIZbiMIQpzyL1YQBI3pcEEQxgmCcEEQhAsF4ksNnSVnhlCY/kaZJk0asmz5PKZMWaAhN3CgC0eOepZiWCnGltSrpI1bF2q1rMepbV4A3Iy4TMLpWL51/4ERm6aQdOk2BfJ/+OR+qWVUumhrty6Yt6xHqNKeWxFXuHE6jsnu3zN80xSSL93WuLmo6yolrLgyQaDV0uHEfr//LxhQmp5SFJUw6unps9ztPpok12/IjYrDZLVij2aVYU48C7ugNrB4s5q3+9fbGDi6H2dOxagNLP5O/qXKIDJ3wVR+27qL589z1eIqV6lEH8eetGnRg+afdcHAwICu/TTPPrxNZyFd+9lQr0UDPH/3UAuvUrMqUzZM55dZm9TSlm6P+u/Sq04hdPFCPB3a9qG7TT9mzJxAmTL6SCQSDKtVZcf2/XTt7Mqr16+xtGpeIs/S9b6pfN9W7sOGT+KndUuJPuPNs2fPkRco/P1y/DXaNO/Bj8s2knD1JrsOFBuQvUF/uuwhrZv1wK5rf5YsXMWv29dRoWJ5NTm3AY54HPPRSF8apdXT+T1BbOo2g+BVh+g2xU0trkZDM+zmfY7XfPVB8N/2O1HEsnVz5HI5HZrZ0621I2O/GUmtOmb0cOjG48cZqm0j76/n/ewsibPLcOpYWFNGX1+1yvBWvbyPfaArkdC+Q2u++Xo2fXsPo4+zHV26dSiW7t3X+y67mzRpyPLl85g8eb6ajKvrSOrWbUuZMvrY2HZ6P12ldbpKmQsX4mnftje23dyYOWui2lmJ8uUN2HvgF+bNWcbLV69LyeL9bDp2wBNZajoewXtZuHwml87Hk5+vaDMzJyzC2WYIXziPxbpDK5wG9X5nfu9LeupDhvQcTd+OQ3Ae3BvD6uoDr9LK7n06o3e120lfz8K2kyuufYbToZO12pmKN9nxd8quEKd+Dni7+5dizL+A/9EzBv8NA4NGwDZRFFsCOcAkYIsoim1FUWwOlAOci8nriqLYDpgGLCkWbgUMAVoAQwRBqCUIQnVgEWAnimJr4AIwo1ial6IodhFF8dBbrq+8KIqdlNf1pzLseyBWec0LgD3K8FnAN6IoWgFdAY2N6qIobhNF0VoURWtZWjbmZkUHwszMTFTbgwpJlcpUMhKJhEqVKpKRoVhCNzUz5uCh3/l67AwSE++rpWvRogm6uhLiYjV3amXJMqhiWjSDWtnEkOyHmRpyn3Vujv3kfuwYu1ZtNi546wnWOc7jtxErQRB4lJimkfZTkl3Cniom1cgpxZ6GnZvTc7IbO8euU7MnZOsJNjjOZ5vSnseJMo20heSmZWBQTJeBiSEvZFmq33oVylKlcS16HF+Ey9mNVG/dgK67ZqoOIL8vebLHRSsAgK5xdfIeZqjJFGQ9RVTuDc464k/Z5ooZ3nJWTag63Jn6p3ZSY95XVHLrSY1Zo0vV8zDtEUamNVW/jUxq8Pg9BhQALds0Y/CY/pw8e5hvF0/CcWAvJi9QP4ybmirD1LxottHU1FjTx1NlmJkrDqsV+nhmRhatrS1Z8sNsLl05xfiJo5g2awJfjRuOjW0nkpNTePIkk/z8fLy9AmnUprEqvwzZE6qZFJWdoUk1ta1GhbTobEn/yYNYPXYF+cX8oVyFcszf+R0H1+3jduwttTRSadG1ApiZGSNLS1eTSZWWsKeywp7i3Lp5l+e5L2jatBEJCTd59eo1Fy8oVrHu35dSscTDtTQljVrmRf1A5cqVyMjIRCotCgcwNzMhLTVdTV4VrrzOmLMXse3Rn46dnYmIiCE5KQVTMxOePX1O7vNcTM2MuXA+Dl1dPdXsYlpqOmZmRTZVrFSRzMwsXr/OIzNTYdvluGskJT6gfoMiX2/avBG6urpcVm7tKE6OLINKxVbnKpkY8jQ9S0OukKue0TQutkWwkrEhn2+bjseM38i8r+5TaanpmBSb5TY2rUm6TF1GlpqOiXJ2X2FTBbIys+k7sA/hp6LIz8/nyeMMLpyNo6VVM9q0t8Kuty0Rsb5s/mM1nbq2Zczoz9XK2czMhNQS/iCVyjA3L70PfxevXr3C2ycIlxJbTFNT0zEtZp+JqVGp7cq0lDpLTU0n+sx5MjKyePHiJSFB4bS0LNreobje4j5uQmpqSZvS3miTmZkxhw9vY2wp9yWVTd5BODnZKe5vxXSZmpmQJtO0w7xE/1Cy/G7dvMvz57k0bao4q6Grq8u+A79w5LAnXp4BirouNlNtbGrEwxL9nCztIcZKGYlEQgWlP8jlclZ+tx7X7kOZOHImlSpVJPmewq502SMAnj/Pxcvdn+ZWTVT5PUx7iLFZUd9a06QGj9Lfr28tzuP0J9y7mUir9upbXNOk6ar6BcXzgEym2Q7+arst9KPnz57jftSb6kbVPkrZATRu1hCJroRrl9W3GWr5uPw3DAweiKJ4Rvn/fUAXoLsgCGcFQbgC9ACaFZN3V/57EbAoFh4iimK2KIovgQSgDtABaAqcEQQhDhilDC/k8Htc30EAURTDgUqCIFRRXuNeZfgpoJogCJWBM8B6QRCmAlVEUcx/Q54KAy7GU7+BBXXqmKOnp8fAgS74+Kgvqfn4BjFsuOKtKv36ORIWFgVA5cqVcD++kyWL1xATo7kNYtAgV44e9SpV74P4u9SwMMbQvAYSPQmtXDpxLUg9D7NmFgxa+TXbx67l2ZMcVbigI2BQpQIAJo1rY9q4NjcjLr/NzI/Og/i7VC9mj5VLRw17TJtZMGDlWHaOXfdOe269xZ6MuHtUrGtM+Vo10NGTULtvB1ICi3TlPX2Be/MJeLWfhlf7aTy+dIeI0T+RcTnxjXmWxssrt9C3MEXP3Aj0dKnk1I1nITFqMpIaRTNIFXq2Vx1MTpu1lru2o7nbYwyPVu0g50QIj9btKlVPQtwNatc1x7SWCbp6utj37Ul44JlSZUvy3eRluLQdRN/2Q/j5h1/wPRbAlpW/q8nEXrxCvXoW1Fb6eL8BTvj7hqjJ+Pue4vMvFIfUXN16ExEWDYBL76G0btGD1i168Puvu9m47jd2bNtHSkoq1m2tKFeuLADdbDqScidFld+d+NuY1DWhZq2a6Orp0tmlKxeC1A/gWzSry7gfJ7L6qxXkPMlWhevq6TJ723zCjp8mxjdKw+ZLFy9Tv35Rm+0/0BnfEvb4+oYwdFh/ANz69SFcaU+dOuZIJIpdi7VqmdKwYV2S76cQEhyBICjs0NPTw9HJjnMx6tvQvLwDGTFCsbA5YIATp0PPqMIHD+6Lvr4+Fha1aNCgLufOx3L+QhwNGtTFwqIWenp6DB7cFy/vQABq1FA8jOvr6zN71jdsXr+NevXrYNW6BXp6erj1d+R+0gN0dATVA1iA7ykGD1XM1ru49SIyXOGL1apVVb1dpo6FOfXq1yE5qeiQd/+BTm9cLUiNv0e1usZUqaVot81dOnCzRLs1tCh6IGnYw4qMJMWgvWwlA4bunEXwmsM8uKA+eAO4HHsNi3q1Ma9thp6eLi79ehPsF6YmE+wfyoDPFW8w6+NqT3SEwkekKTLVHulyBuVoZd2Cu7cTWbtsE51aONC1lSNTvp5LVMR53PqNpkEDi6JyHuSKt7d6H+7tHcSI4QMV5dHfidDQt7ev8uUNMDZWPFBKJBJ69+rBzZvqZ2ziLl2hXv061K5jpqizAY4E+p1Wkwn0O83gLxRvs3Hu24szyjoLDYmkSbNGlFOe0enYua3agdULF+Jp0KAudeoobBo0qJT7kk8ww4YNUNpU4r7kvpPFi9cQHV102FzDpt7duXXrLhcvXqZesfY0YKAzvj7Barp8fUL4QqnL1ai5RQAAIABJREFUrV8fwt7Unj6rR/J9RT+w9ddV3Lx5l62bFStJV2ITsKhbC/Papujp6eLk5kCIv7o/hPiH0X+IYg6yt0tPYiIV56bKlitLOQNFX9PZpj1yuZw7txKRSCRUVQ6cdXV16e7QRe1w+7W4G9SqW0vVt/bqa0dYwPv1rTVNalCmrGL1o2Llili2bUnyXfVBVmxJH+jvSIDvKTWZv9puJRKJajJAV1cX+962nI04/8HLrhDn/r3xdg94rzL5RxALPv7fP8B/w1uJSq6ticAvgLUoig8EQVgKlC0WX3hSS466fcVPcBXGCUCQKIrqR/6LeP43r6/0RTxRXCUIgg/gCMQIgmAniuIbh8JyuZyZMxZz0nMPEomEPXuOcP36bRZ9N51Ll67g6xPM7l1H2L5jPZevhJKZmcWokYo3b4yfMJJ69eswb/5U5s2fCoCrywgePVLsQ+w/wIn+/caUqrdAXsDxxTsZv2cBOhIdzh45jex2Cr2nD+LBlXtcC76I6/xhlDEow+hfFG+HyZQ+ZsfX65Do6TLl6FIAXj57wb7pW/72VqLZS1ZxPvYyWVk59HQbzqSvRjDApde7E5Zij8fiXXy9Zz6CRIfzR0JJv51Cr+kDeXAlkYTgizjPH0oZg7KM+OVbALKkT9iptOebo0tU9hyYvvWt9ojyAi4s3IXtgbkIEh3uHQoj55aUFrMHkBGfiDTw7Yd9Xc5uRK9COXT0dTHvZc3pL1ZpvNEIAHkB6T/8Sq0dy0GiQ/axQF7fuU/1qcN5efU2z06dxXBkXyr0aI8olyPPekravPV/uezkcjlrFm5k04F1SCQ6eB7y5d6tJMbP/pLr8TcJDzxDU8vGrNmxnEpVKtLFvhPjZ33JkO7vft1qYf7zZv/AUY8d6EgkHNh7jJs37jBv4VTiLl3F3+8U+/cc5ZdtazkXF0RWZjZfj5n+1jwvXbiM18kATkWcID8/nyuXrxN8oOjmUiAvYMfibSzcsxQdiQ6nj4SQcvsBQ2YM5e7lO1wIPseIBWMoa1COmb/MAeBx6mNWj11BR+fONGnXjIpVKtJ9oOIw59ZZm0hKSFTZM2vm97if2IVEosO+vce4cf02CxZNI/bSFfx8Q9i7+wjbtv9EbPwpMjOz+HK0wuc6dLRm+szx5OXlIxYUMHP6EjKeKFa2Fi1YxdHjO9DREbh37z4LF6xg6ZJZXLgYj7d3EH/uPMTuXZu4kRBJZmYWQ4crXouZkHCLY8e8uBJ/mny5nKnfLlTtf/922iJ8fQ4g0dFh1+7DJCQoHqBnzZiIo5MdOjo6/P77HsJDo5k/axn7j/ymXN3IZtykUUSERdOrT3cC/E5zYO8xtmxbQ0xsAFmZ2Yz/UrHw2qFzW+YsmII8X468QM6c6UvJyiwaaLn268PQgZqvqC2sJ9/FuxixR9GWYo+E8ei2lO4zBpB6OZGbwZdoN8qBel2aU5An50XOczxm/AZAu1EOGFoYYTOlHzZTFIPKvSNW8Vw56JfL5SyZ+yN7jv6KjkSHowdOcPvmXabPm8SVuGsE+4dxeJ8HG35dwenzXmRn5TBlrMIX9u44xNrNPxBwxh1BgGMHTnIj4XapNsjlcqZN+w5vr31IJBJ27T7M9eu3WLx4JpcuXsbbJ4iduw6x88+NJFyLICMjixEji14de/NmFJUqVkRfXw8Xl144OQ8jIyOT48f+VG4z0yE0NIptf+yjkl45Nb0LZi/n4PHtSCQ6HNznzs0bd5izYApxsVcJLKyz31cTfclfWWeKrYbZ2Tn8vnUX/qeOIooiIUHhBAeGqeU9ffpivLwU96XduxX3pe++m8GlS5fx8Qlm167D/PnnBq5eDSMzM4sRIyYDMGHCKOrXt2DevCnMm6e4V7m4jEAQBI4d246+vmLrXFhYFDu2H0AulzN75lI8Tu5GItFh756j3Lh+m4WLpnFJ2Z727D7Mtu3ribt8iszMbMaMUtzvOnayZvqMCeTl51NQUMCMaYvJeJJJh47WfDG0P1ev3iAyWnHGbtOPv/H9/DX8eWQLEh0Jxw6e5M7Ne3w7dwJX4hI4FRDO0f0nWffLMoLPnSArM5vp4xTbc6tVr8qfR7YgFojI0h4ya9J3gOJQ8J9HtqCrq4tEokNU+Dk89nmplePqBevZenA9OhIdPA/5cO9WIhNmf0VC/A1V3/rTnyupVKUi3ew7M2H2VwyyHUHdhnWYsWSycrsg7P3tIHduFA06CvOfP2sZh9x3KH3guMoH4mOv/q12a2BQjkMeO9DT1UVHokNEaDQHd7uT8iDtg5ZdIY6udoz94ttS25aWj4fwV/a0fWoEQbAAEoFOoihGC4LwB3ADmINiNUACxADHRFFcKghCKDBLFMULym1CF0RRtBAEYTSKgcRkZb7ewDrgGoqVhR6iKN4RBMEAMBdF8ZYgCEnKNG9c21PquyGK4gRBELoAv4qi2EIQhE3AI1EUlwmCYAtsEEWxlSAI9UVRvKtMewLYJYriiTflX97A4pNUzria7343/4dizYWVn0TPfOuFn0RPm9efbtGtVQXN7U8fgxHPnn0SPQCJz968LetD0r1qk3cLfQACn3y6l6g9f615BuljUK3cf/5msPdhYhXNvcofi93PPk09pT7X3KL2sahatsIn0ZP9KvfdQh8APZ1P984PI4N3H/b+EBR/XenHRpr717cl/R0q6Zd/t9AH4vaji6VNuv5jvAjZ9tGf0cr1HPfJbf5vWDG4DowSBOF34DbwK1AVuAIkAaW/B/E9EEXxkXLQcFAQhDLK4EWA5trzm8kUBCEKqAQUfulmKbBTEITLQC6KLUoA0wRB6I5ixSIB0HwVhxYtWrRo0aJFixYt/wD/6oGBKIpJKM4AlGSR8q+kvG2x/z9GecZAFMVdwK5icc7F/n8KaFtKXhbveZnHRVFUe7WCKIoZgManCEVRnFIyTIsWLVq0aNGiRct/Gf/QGYCPzX/D4WMtWrRo0aJFixYtWrR8ZP7VKwb/FgRB2Ap0LhH8c/EVCi1atGjRokWLFi3/T/iHvjPwsdEODN4DURS/ebeUFi1atGjRokWLFi3/vWgHBlq0aNGiRYsWLVq0/BX+R88YaAcG/2J0P9Hr2janRnwSPQCST/Qa0R8vrPgkesZbz/kkegBycw0/iZ6svPR3C30gXuS//iR6Lj7X/MKqlvfjWd6neS3qirTQT6IHoIL+p3tt5KficW7Ou4U+AOX1y75b6APw8hP1DQADyzf6JHp2ZcV9Ej0AZSR6n0SPsX6VT6JHy6dDOzDQokWLFi1atGjRouWv8D96xkD7ViItWrRo0aJFixYtWrRoVwy0aNGiRYsWLVq0aPlLaFcMtGjRokWLFi1atGjR8r+KdsVAixYtWrRo0aJFi5a/gvatRFq0aNGiRYsWLVq0aNFuJdLyj9DTrhsXLgURG3+K6TPGa8Tr6+uzc/cmYuNPEXL6OLVrmwHQuk1LIqK8iIjyIjLaG2cXB1WaypUrsmffFq7diOBRxnWS7l1gzmzNb7jp6+tzYP+v3EiIJCrSizp1zFVxc+dM5kZCJNeuhuNgb6MK/2PbT6SmxBMXG6KWl6VlM85EeDHd90e+9VxBLcv6ADSysWROyE/MC91A94muGtfQ7StHZgetZYbfasbvX0hVs+qqOKd5XzArYA2zAtZg6dzhfYu0VBatXE83p89xGz7hP8oHoLmNFStDfubH0M04TnTTiHf4ypnlQRv43u8nZu1fQrViNm2/e5ilvmtZ6ruWKX/MfaseM9uWDAhby6DIn2j5jYtGfOPhPegX/CNuAStwcv+OKg1NAdDRk9D1p3GKuMAVGHdsopG2a4+OBEQfJ/jcCcZNHa0Rr6+vx8Y/fiT43AmO+e/GrJYJAHp6uqzatATvsMN4nj5Iu05tVGn09HRZ9tNCAmPc8Y86Ti/nHgDY29sQGxfC5SuhzJw5sRRd+uzes4XLV0IJDTtB7doKP+zRowuRZ7w4d86fyDNe2Nh0VKXx8z9EbFwI0TG+RMf4Uq16Vbr16ERwjAenzp1kwtQxpdq0afsqTp07iXvAHpVNurq6rN3yA37hRwiMOs7Eb78EoG6DOnifPqT6i0+MYOKk0R+1zZ6/FMjV6xFcvR7OjYTID9Juy5QpQ/QZby5eCCI+7hRLFs9Uye/ZvZnYuBASrkeQmnaZK1fDPngdXbkaRkbmTW7djGb2G+zZv/9XridEcqaEPXPmTOZ6QiRXr4ZjX6wfun0rhthLwVw4H0hMtK8qfNWPi7hyJYzIGG/8gw9zIT6Yi/EhTHtDPe3Y/TMX40MIOn2MWsp6KsTc3IQHsngmT/0KADMzEzx99xFz0Z+o836MnzQKAAd7W65cDiXhWgSzZk0qVc++vb+QcC2CiHBPlX2GhlUICDjMk8c32LhhmUY6gOPH/uTWzSiuXA79JP6w7fd1REZ7E381FGlaPHFXTn8QH2/QsK4qPCLKiwepcUyZ/NVHKz8vz72cPxdA7KVgtmxeiaAjqMV/ZtOSGSHrmBW6HpuJmn1ru2E9+dZ/FVN8VzL+6BJqNlDYZ1ClAmMPLmTptT9x/X60RjqA7j27EHHeh6hL/kyeNrYUe/T47c+fiLrkj0/wIcxrm6rimjT7DK/AA4RGe3LqzAnKlNEHQE9Pj7UblxJ5wZeIc944udoDYNOzM6fPehJ+wYdJ335Vqq6tO9YSfsGHk0H7Ma+l0OU20Am/sKOqv6TH8TRt3ojyFQzUwuNuhzPle/U6aWfblv3huzgYuYdh33yuodOyfQt2+P/G6eRAbJ26qcXVNK3JTwdWszf0T/ae/hNjc6NSy1DLx0U7MPgXo6Ojw0/rlzKw/5e0s+7FgEEuNGrcQE1m5KhBZGVl08qyB79s3cn3yxQPk9cTbmHb1Y2unVwY4DaGjZuWI5Eovouwas1iQoIjyHudR8d2jli368WQIW40adJQLe8vx3xBZmY2jZt2YeOmP/hxpeIbBE2aNGTw4L60tOqBk/MwNm9aiY6OwpX27DmCk/MwDVtWrVzIsuXr2eA4n4D1R3GePxRBR6DfD2PYPno1a+1n0cq1E0YN1G++0oQkNrosZH2fuVz2O4vT/KGKa+jeCrNmdVnvOI9Nbt9hO86FMhX+/rvJ3Rzt+W398r+dvhBBR4fhP4xlw+gVLLKfTnvXLpg2MFeTuZ+QyA8uc1nSZyYX/KIZNH+EKu71y9csdZzNUsfZbP569Vv0CHRaPorAEWs43n0O9fp2UD34F3L3RDQedvM50WshV371of2S4QA0GtodAA+7+fh/sZr23w0FoejGqKOjw9JV8xj7+VT6dB6Ic79eNPisrlreA4e5kZOVg107N3b+tp/Zi6cCMHhEPwCcbYYwetAk5v8wHUGZ98TpX5HxOAOHDv3p03kg56IuoaOjw/oNP9DPbTRtWtszaJArjUv4+KjRg8nKyqZlC1u2bN7BsuXzAHjyJJOBA7+iXbvejPt6Jtt3bFBL9+WX0+jYwZGOHRzJzMjm+9XzGDNkMr06D8Clf28afFZPTX7wMDdysp7So11f/vxtP3OXfAuAY1879Mvo06fbYFx7DuOLUQMwq2VC4p1knLt/jnP3z3HtOZSXuS/x9Qn+aG02OCic9ta9yc/P54vB42hh2f2DtNtXr15h5zCYNtb2tLF2oJeDLe3btQbg4EEP2rS2Ry4v4EzkObZs+fOD1tHYsTMAaN3KjmbNu/H5G+zJysymSdMu/LzpD1YWs2fI4L5YWvXAuUQ/BGBnPwjrtg506OioCgsOCcfKqgfdOrnSqHEDwkOj6GDdmwGDnDXqacSoQWRnZdPGsie/bt3J0mXq3yxZsXohwUHhqt/5+fksmv8jHdr0xqH7QMZ+PZymTRvx88/Lce07EkurHgwZ3JfGjdXtGzP6c7KysmjarCubNm9nxfIFALx8+Yrvv1/HvHml90t9+/bmee5zTEyMcO078pP4w8xZS+nW2RWxoAB3d1/27TnyQXz8zu1EunZyoWsnF2y69OXFi5ec9PRHR0fno5Tf0GETaduuF61a21G9ejVaOBVNLAk6Aq4/jGHn6DVssJ+NpWsn1YN/IfEno/i59zw2Oy4g/HcvnL5T9K15r/II+ukYviv3l1pnOjo6rFy3iGEDx2PT3gW3gY581qi+mswXIwaQnZVDp9a92fbLbhYtVQzMJBIJW7atZu6M77Ht6MoA51Hk5eUD8O2s8Tx+lEEXa0e6tXchOvI8Ojo6LF+zkFGDJ9GzY19cB/ShYSP1Pm/I8P5kZ+XQzdqJ7b/uZf7S6QCcOOZDH5tB9LEZxLQJC0i5n0rC1Zs8f5arCu9jMwjpgzTCfYu+g6Sjo8OMFVOZNXw+I7p/iZ1bDywa1lHTmS59yMrpawg+oT55CLDo57kc/PUII2y/ZJzTJDIfZ5Vajv8axIKP//cPoB0YvAFBELYLgtBU+f8F/0E+voIgaHwBRBCEpYIgzHpb2jbWlty7l0xS0gPy8vJwP+aNk5Odmoyjkx0H9rsDcMLDDxtbxYzcixcvkcvlAJQtWwZRFAGoWLECnTu3JSHhFvfuJXPnTiKPHz/hyJGTuLr0Usvb1cWBvXuPAnD8uA89undRhvfiyJGTvH79mqSkB9y9m0S7tq0AiIg8S0amZmMWRZGKlSoqrqeSAdnpmdS2asCTZBkZDx4iz5MT5xVNMwdrtXR3oxPIe6n40E1y7B0qGys+8mXU0Iy7Z69TIC/g9YtXpF5PprGN5duK861YW7WgsvL6/hPqWTXgYbKMRw8eIs/L56zXGawc2qrJ3Ii+xmulTfdib1PVuNpf1lPDqj45Sek8vf+Igjw5907GUNuhjZpM3rMXqv/rGhT5QJWGZqSeuQbAyyc5vM7Jpbpl0YN/y9bNSE56wINkKXl5+ficCKRnH1u1vO362OB+2BsAf68QOnZtB0CDRvWICj8HQMbjTHKyn9LCqikAA4e68tvPOwGFP2RmZGFtbcW9u0U+fuyYF87ODmq6nJ0c2L/vOAAeHr7Y2nYCID7+GrK0hwAkJNyiTJky6Ovrl1pelq2bk5xYZJO3RwD2GjbZcvyQFwB+nsF0UtokimBgUBaJRELZsmXIy8vj2dPnamk7dWtHclIKNY1qfLQ2u2f3EUWfcDeJK1dukJeX98Ha7fPnuYBiVUdXT0+l28//lKqOwsKiMTau8UHrqEmThmr1f/jISVxK2OPyBntcXHpx+A32vIng4HDkcjltrC25nyylQoXyynrywbFEPfVxsuPgfg8ATnr4q+oJwNHZjuTEB9y4flsVlp7+iMvxinb17Nlzbt28S/funbl7N4nExPuK+jrqiYuLetm5uDiwd98xANzdfejevTMAubkviIo6z8tXrzTsKF/egG+//Rpv72Bev84ryv8j+8PTp89U96W8vDzy8+UfxMeLY2vbicR797l/X0rbtlYfpfyePn0GKFYD9fX11K6jllUDniSnk6m8L8V7RdOkRN/6qljfql+sb8178YrkCzfJf5WnoROgVZsWJN27z/3kFPLy8jh53I9ejj3UZHo79uDIwRMAeJ8MpKuNYtBi06Mz16/eIuHqTQAyM7MpUG5l+XxYPzZt+ANQ9K0ZGVlYtWlBUmKhrny83P1w6NNdTZeDY3eOHfIEwPdkEJ27tde45r4D+nDyuK9GuEW92lSrYUj82SuqsCatGiNNkpJ2P438vHxCTp6mS69OaulkKencvX4PsUC97i0a1kGiK+FCxEUAXuS+5NVLzbrT8vHRDgzegCiKY0VRTFD+/NsDA1EUHUVR/FvDXlNTI6QpaarfUqkME1P1pTUTU2OVjFwuJyf7KYbVqgKKgUXMeT+izvoy/dvvkMvlWFjU4vHjDBYvnUWrVi3YvGUlBgblSJGmYWpqrK7fzJgHKamqvLOzc6hWrSqmpkXhgCKtmXraksyYtYTVPy5iUdQWXBYMw2/NISobVSUr9YlKJivtCZWNqr4xj/aDbbkRGg+gGAjYWqJXVh+DqhVp0LEpVUz++gP2h6aKkSEZqY9VvzPTnlDV6M1fLO46uAdXQmNVv/XK6LPYczULPVbSqsSAojgGJlV5npah+p0ry6C8iWbZNRllx6DIn2i78HNiFu8BIOP6feo4tEaQ6FChVg2qtbCggmlR2Rmb1CRNWvT1Y1lqOkYmNdTyNTKugUwpI5fLeZbzjKqGVbhx9RZ2fWyRSCSY1zaluWUTTMyMqFipAgDT5k3kRMh+Nu1YTbUahpiaGpEiLfIlqTRNw8eLy8jlcnJynlKtmrqtbm59uBx/jdevi76W+vtva4mO8WXuvCkKm1KLbEorzSaTmqRJZSo9T5U2+XkGk5v7kphrQUTG+fHH1j1kZ6l/ZdalXy+83P0/apv95bc17PhzA7Vrm2NgoFgd+1DtVkdHhwvnA0mTXiYkJJxz54t80tTUiNRUGV8M7UdQYNgHraNFC6fTuk0L5s6boiyvNMze0x4zU2NSUtR9p9AeURTx8z3I2Rg/xn6luYJpYmpEVcMqBAcqZvxTS6mn4nWpqKdnGFarioFBOb6dPp7VP27WyLeQWrXNaGnZlMzMLLUyL9W+Yna8qexKsnTJbDZu/IMqVSqRl1f0EPop/GHxkpl06tyOhp/V5/ff9nwQHy9O/4HOHDvmpSqbj1F+AN5e+0h5EMvTZ8+56ntWFV7JqCrZxe5LOWkZVC6lD+8wwp5ZYRvoPW8oXkv3vFMfgLGJEVJlHwOQlirD2KSmhkxqsX4oJ+cphoZVqN+gDiIiB49vIzDsGJOmKrY0VqqsmNCau3AKgWHH2LZrA9VrVMPYpKYqH4WudIxMjEroqqmmq7DPK45Lv96cdPfTsKXvAEe8PPzVwmoYV+dh6iPV70dpj6huXL1k0lKpVc+cZznPWf7HUnYE/MakRePUVgD/lRQUfPy/f4B/eal/GgRBKC8Igo8gCPGCIFwVBGGIIAihgiBYC4KwCignCEKcIAj7lfLDBUE4pwz7XRAEyVvyThIEobry/wsFQbgpCEIwUOo32AVBGCcIwgVBEC7I5S814ktOsAiChohq9uLihXg6tO1Dd5t+zJg5gTJl9NHV1cXSqhmnQyLw9grkee4L5s6ZrJau2LWUqr/0cM2Zn+KMHzeSmbOXsrzTZDyX7WXQ6nGlXvybsmnt1gXzlvUI3aa4YdyKuMKN03FMdv+e4ZumkHzptsYN5p/gr5RNB7euWLSsj/+2k6qw2Z0m8IPrXLZN3cgXi8dQo/ab9li+X9ld3x3M0S4zOb/yEFZTFecdbh0K43laBn19l9Fh6XAeXrxNQX6xsnsPG95k57EDnshS0/EI3svC5TO5dD6e/Hw5urq6mJgZc+lcPG49hxF7/jLzlk57v/J6h0yTJg1ZtnweU6YUjd+//PJb2rXrjb3dIDp3aqt21qEoj5JqStdj2boZBXI5HZs7YNPGibGTRlCrTtHWAj09XXr2tsHPM+iNbeYd5rxXm92xfT+Lv1tNfn4+02dO0Ej7djve7psFBQVYt3WgTl1r2lq3olmzou5JEAQ6dGzDmchzREWdL1Xn362j+fNX4OcbQudObRk+fOAHs8fG1o127Xvj7DKciRNH06WL+kyoa99eiAUFHDl8UiPtu2yat/Bbft26UzWrXpLy5Q3Ys38r8+cu52UpM56a9mnm8bb+tGXLptSvXwdPT//3aj8f2h92bN/P0SOe3Lp5h/4DnFT5va9Npfl4IXp6ejg69eSEh+9brv0/K79CnF2GU8fCmjL6+tTv1OytGZaWX8zeINbZTMd/1UF6TNE8S1YapdrzPjKiiESiS7sOrfnm6zn07T2cPs52dOnWAV2JBDNzE86fjcXBZiAXz8exZPns/8A3imSs2rTgxYuX3Lp+R0POtX9vPI+XGDCUUhdvvKmXQKIroWW75mxd9jvjHCdhUtuEPoN7vTuhlg+OdmCgoDeQKoqipSiKzQHVMFgUxXnAC1EUrURRHCYIQhNgCNBZFEUrQA5oTkmVQBCENsDnQCugP1DqdLAoittEUbQWRdE6PT0bM3MTVZyZmTGytHQ1+VSpTCUjkUioVLkimRnqCxS3bt7lee4LmjZthFSahlQqIyLiLGbmJpw84UcrqxaYm5mQViJvaUoatcxNVXlXrlyJjIxMpNKicECRNlU9bUlGjhiEh7Kzj/eJobZlfbJlGVQpNlNdxaQaOQ8zNdI27NycnpPd2Dl2HfLX+arwkK0n2OA4n20jVoIg8DhRppH2U5Mpe4KhadEMSVWTamSVYlPTzi1wnjyATWNXkV/MpkLZRw8eciPmGrWb1dVIC5CblkF5k6JZLANjQ3JlmnoKuXcyhjq9FA/HoryAs9/v50SvhQR/tQH9SgbkFCs7WWo6JmZFAxJjUyMeyh6r5SdLe4ixUkYikVChUgWyMrORy+Ws/G49rt2HMnHkTCpVqkjyvftkZmSR+/wFgT6nAcVWnWYtGyOVyjA3K/IlMzMT1daTQlKLyUgkEipVqkiG0sdNzYw5eOh3vh47g8TE+6o0hf747NlzjhzxpIZRNbVZTRNTIx7KHlEchd3GKj0VlTa5DuhDWEgU+fn5PHmcycWzcartUQA2dl24dvkGjx9lIC3WHhX2fLg2e/FCPFKpjNzcF1haKh5kPnS7zc7OISw8il4OtqqwnnbdqFKlMnPnLlPa9OHqSCqVYWRUkyNHPGlrbYWZmQmp72lPijQNc3N13ym0p7BMHj16womTfrRta6WSGzFiEE2afsa9e8mqMFMz41JtUq+nCortb20t+X7ZHOKvhTJx0mhmzJrI1+MV54R0dXXZvX8rRw974u0ZqFHmpdonlansKFl2pdGhfRtatWrJzZtRLFo4ncqVKxEYeAT4NP4glcowMzPG/bgPrn17fxAfL8TewYb4uGs8evhEqevDl19xXr16hbdPEE3ti7aw5sgyqFzsvlTJxLDU+1Ihl72i1dK/jbRURdkVYmJqTHoJv0tLlalWbgrtycwpBO2uAAAgAElEQVTMJi1VRvSZ82RkZPHixUtOBYXTwrIpGRlZ5D7PxdcrGACvEwG0aNmUtNR0tZV8RZ9XUle6mq7CPq8Q1/6lbyNq0uwzJBIJV+IT1MIfpT2mpmnRSmwNkxo8Tn9SMnmpPEx7xO2rd0i7n4ZcXkBkwBk+a9Hw3Qn/SbRnDP6nuQLYCYKwWhCErqIoZr9FtifQBjgvCEKc8ne9t8gX0hXwEEUxVxTFHMDzXQkuXbxM/foW1Kljjp6eHv0HOuPrq35gx9c3hKHD+gPg1q8P4WHRANSpY646uFirlikNG9Yl+X4KDx8+RipNIycnh/r1LXDt25ubN+8weHBfvLwD1fL28g5kxIhBAAwY4MTp0DOq8MGD+6Kvr4+FRS0aNKirttRcGqlp6dh0U+wzbdCpGY+TZDyIv0t1C2MMzWsg0ZNg5dKRa0EX1dKZNrNgwMqx7By7jmdPirZvCDoCBlUU21NMGtfGtHFtbkVcfleRfnQS4+9gZGFCdfOaSPR0ae/Smbig82oytZvVZeTK8Wwau4qnxWwyqFQeXX3FG4QrVK1IwzaNSbudUqqeR/H3qFTXmAq1aqCjJ6Fe3w7cD7qkJlOpbtGDcK2eVmQrH/4lZfXRLVcGANOuzRHzC8i6XbRcfyU2AYu6tTCvbYqeni5Obg6E+Iep5R3iH0b/Ic4A9HbpSUykwsay5cpSzqAsAJ1t2iOXy7lzKxGAU4HhtO+suIF26taOO7cSuXgxnvoNinx84EAXfHyC1HT5+AYxbPgAAPr1c+T/2DvvuCiO9/G/545i71LtJcaOirF3xYKI3dg1lsRo7L1rjBoTY4saSxQVC3alqGBBQbEggoVqQaRLsxvh2N8fhwfHnYIJ8sk3v32/XveC3Xlmnn1mZ56d2Sl78eIVAIoXL8bRIztZtHAVV69mlhulUqmZSmBgYECXru256n2DSlUqaGzq3qszZ0976tjU52v1DiRde3TEx0ttU3RkLM1bqfvxBQsVwMq6Hg/DwjXx7Hp3wfmo+l3C56yz1apXxu/mbapUrURMdByGhoZ5Um/LlClF8eLF1PevQAE6tG9FSMgDQL1wtWbN6rx+/YYKFSzz/B7dvBlAtWqV6N3HluDg+wzob49LNntcPmCPi4s7A/TYU6hQQYoUKQxAoUIF6dSxDffuqedl29i0Zfr07+nVYwSVKpWnguY+2XIq23067XaOgYPVi+nte3Xh0sWrAHSzGUj92m2pX7stmzc58Nuvm9m2ZQ8AGzatIDTkPpt+3wGAr6/avkqVyqvvV78euLho552LiwdDM0ZLeve2xTPDvg+xddseKlexpkaN5rRp25O0tDTGjp2WL+WhatVKmjI+YIA9D+6H50kZf0/ffnYcPuSsOf4c+Ve4cCHMzNTTd5RKJV06t+fpgyxTqjKeSyUznkv17ZoRlO25VLpSZoO7RvsGJITn7qWUv99dKletSPmK6rpk36crZ05d0JI5c+oC/QeqRyC629vgfUk9zcnz3GVq1a5BwYLq9U5NWzQmNET9Jt/9tKdmTVTLNk0JDXlAgN9dKlepSPkKlhgaGmDXuyse2XyexylP+n6t3g2wm30nrnhd14QJIbC1t9H4tqzY9+nGST3Ti4L9gylX2RLz8mYYGBrQwb4d3u5XcpU3wf4hFC1RlBKligPQsEUDwkMf5xBL5nMgf8cAkCQpNOONfjdghRDC/SPiAtglSdKcv6PqU4RVKhXTpy3h6HEHlEoFjnsOExwUxtz5k7nld4dTbufYs+sgW7ev5lbAeZKTU/hmhHonlabNrJky7VtSU9OQ0tOZNmURSYnqtx4zpy1hy9bVIATDhvfnaUIiO3bsJzAwlMWLpuN7MwAXFw927DzALof1BAd6k5ycwqAh6m3JAgNDOXzYmTsBF0hTqZg4aZ5mEZTjno20ad2MMmVKEf7QlyVLf2WnwwG++24Gv/22FPOCxUn7K5VDc7aTrkrn2EIHxuyeg1AquHHQk7iwSDpP6cuTO48IPHuT7nMGYVyoAEM3qe1KiUpk55hfURoaMP7QIgDevnzDvikbSVf9/d71jEUruXHrNikpz+nQcwjfjxpKH7tPH8ZMV6XjuHA7U3fPR6FU4H3wPNFhkfScMoDwOw/wP+tL/zlDMS5UgO83qXebSIxKYMOYnzGvVo7hy8ciSRJCCNw2HyP6vv6OgaRKx2fBLrrsnYlQKAh1ukhKaBQNp/chIeARER5+1Bphg0XL2qSnqfjr2SsuTdkCQMEyxei8dxakp/MqNpmLkzZrpa1SqVgyZxU7Dv6OUqHk8P4T3A95yKRZ33HHP5DzZy5xaO8Jft30I2evHycl+RlTxqqniJQuU5IdB39HSpeIjYln+vcLNOn+snQ9v276kXnLppGUmMzsiUtQqVRMm7qQEyd3o1Qq2b37IEFBYcxfMAU/vzu4uZ5ll8NBtv/5G7fveJKcnMLwYer56N9+N4wqVSsye85EZs9R74rUw24or1695sTJ3RgaGKBQKvG8cJl9DkeIjIhh16FNKBQKDu07QVjIQybPHscd/0DOnb6I097j/LZpGeevn+BZynMmjlHvrLNnhxOr1i/htPdhhBAc3n+C4ED1otMCBQvQsk0T5k9dpsm7z1Vnt/+5BkMjQ8JCH9K6bTPu3vbEYZfTP6635uam7PhzLUqlAoVCweHDzri6qd8+btq4koiIKCRJ4pb/OV69esP69dvy/B41adKQ6tWrsNPhAIGBoSxaNJ2bWexxcFhPUIY9g7PYc+iwM7ez2WNqWpbDh/4E1NMTDhw4jru7JwDr1i7D2NiYw8fU4ZeunCQpMYW9ew4RHBTGnPmT8Pe7q7lPf2xfzc2AcyQnpzBqxOSP1v2mzRrx9aBe3LsbzKUr6vc+8xesZPLkBbg4O6JUKnHY5URQUCgLF07D7+ZtXFw92OlwgJ071hJ4z4ukpBSGDsvccjQk5ArFihbFyMgQO7vO2HYfTHBw5oJnlUpFTEw8Ls6OKBSKz1oehBDs/HMtxYsXQ6FU0rtvdxITk9mz62CelPGCBQvQrl0LJk+cp2VfXudfUlIyRw7vwNjYCKVSgafnFaL2ZnZs0lXpnFzowDe7ZyOUCnwPehIfFkXHKX2JuvOQoLN+NBtuQ7UWdVClpfHm2SsOTcv0oTO912FcpCBKQwNq2TRix9CVxN+P0tgzd8ZP7D+yDaVSwQHHY4QG32fG3AkE3LqH+6kL7N9zhA1bfuaK32lSklP47hv1HiXPnj1ny8ZdnDp/EEmSOOdxiXMZa2R+WvwbG7asZOmK2SQmJDNl/DxUKhULZi5nz+E/UCqVOO09RmjwA6bOGc+dW/fwOO2Jk+NR1v6xgku+rqQkP2PC6Mydt5o0b0RMdCwRj3WfQd17dmb4AN2tY1WqdNbM38DqfT+jUChwdTpFeOhjRk0fQXBACJc9fPiyfg1++nMJRYsXoXmnZnwzbTjD2o8iPT2djUu3sNbpVxAQeicM532uH61z/3P+o98xELmZi/dfRwhhASRJkvRWCNETGAGUAKZLkuQrhEgGTCRJSs3YqegE6qlE8UKIUkBRSZL0dm2FEOGANVABcACaoO6Q+QFbJEn69UPXVbxI1Xy5Oa/e6a5l+FxMtmids1AesML3p3zR8631zJyF8ogWaQXyRc/Kv4LyRQ9A9KvcDTP/U0wL5bwYMS9IfPs8Z6E8Ir/qrbGBYb7oeZemfyeXz0ERo7+/tfGn8Dot/3ZVUeVTI6WwUf74obdp73IWyiOmmrXKFz0OKf75ogfAUPHBpY95SsWCJjkL5RFeUef0rWL4n/Hm8LLP3kYr2Hd+vtssjxioqQv8IoRIB1KBcUDWBvtW4LYQwi9jncF8wF0IociQHw98dMxLkiQ/IYQT4J8h6/UxeRkZGRkZGRkZmX8p/9ERA7ljAEiSdAY4k+102yzhs4BZWY6dAKdcpl0py/8/AfnzKltGRkZGRkZGRkbmE5A7BjIyMjIyMjIyMjKfwn90Kr7cMcgjhBDXAONsp4dKknRHn7yMjIyMjIyMjIzMvwm5Y5BHSJKk+y1xGRkZGRkZGRmZ/x7/0TUG8ncMZGRkZGRkZGRkZGTkEYN/M29S82eru1qlKuSLHoBG7/KnL5pf24hu8V2VL3oA4mxH54uec7H5Vx7Op77OFz31C5XLFz3n3wbmLJRH5Ncedvm1DWa1Epb5ogeghGHhfNHjl3g/X/QAlClULF/0mBcolbNQHvDgRUy+6AG4qUrKFz0v3r3JFz0AJQrkTxl/rso/m/51yCMGMjIyMjIyMjIyMjL/VeQRAxkZGRkZGRkZGZlPQZJHDGRkZGRkZGRkZGRk/qPIIwYyMjIyMjIyMjIyn8J/dI2B3DGQkZGRkZGRkZGR+RT+ox84k6cSycjIyMjIyMjIyPwfQwjRRQgRIoS4L4SYrSe8ghDighDilhDithCiW05pyh2D/0PY2LTl7p2LBAZ6M2P6eJ1wIyMj9jpuIjDQG28vZypWVG/RWKpUCdzPHCQpMYS1a5flSleLdk056X0AF59DfDNhqE54o6ZWOLk74BfpRafu7TTna9Suzh6XrRy9uJfD5/fQ2b7DR/WYt62HrdcvdL+8mpoT7D4oV972KwZG76VUvcpqW0sWof2hefQN+5NGPw3P0Z46baxYfm4dKzw30G1cT51wm1HdWeaxhiWnVjN97yJKW5bRhG1/4MRit19Y7PYLP2yblaOujzF/+W+0tv2ankO++0fpABg3bYzpwV2YHd5D0WEDdcIL2XbG/PRRTPZsxWTPVgr1yPQHxSeMxXT/DkwP7KT41Akf1VOvTQN+Pf87v13chN243jrh3Ub3YNXZ9aw8vYa5+5ZQxrIsAGUsy/KTy68sd/uNVR7r6DC4s97023VoifcNN3z8TjNhsu6WrEZGhmzZ8Rs+fqdxO3uA8hUsNGE1a3+Bi/t+Lvo4c+HyCYyNjQCYPX8SN++e50Gkr16dDdo05PcLm9l0aQu9v++rE95jtD3rz21kzZn1LNm/jLIZNgEs2L0Yxzv7mbdzod60O3Rsja+fB7cCzjNl6rd67DFi56713Ao4z7kLR6hQQb1NZ8NG9fC64ozXFWe8fVzobmejiVO8eFF2O/7ODT937gZ5cTfoEkGB3syY8QE/sHczQYHeXPbO9AMAM2dOICjQm7t3L9GpUxuteAqFghvXz3D82C7Nud27NnD79gVCQi4TF3eXe/cuMX3693p17tmzkXv3LnHp0gkt33PmzAESEoJYs2apRr5IkcJcu3ZK84uM9GfOj1N00m3ZriluVw5x+toRRv8wTCfcumkDjpzdzZ3oK9h0b68VtvXAOq6FnWOz42868bLTtG1jDlzaxSFvR4aO161LVk3q4XB6C16Pz9LOtrVWmHfEWXa5b2OX+zZW7dT1rzad2nLntieB97w+mHeOezYReM8Lr0sns+WdE4kJwaxd86Pe6z5yeAd+N89qjvO6LhUsWABHpz/wuu7KRR9n5i2aqpNm83ZNOOa9nxM+ToycMEQnvGHT+uxz38GNyIt07N5Wc968nCl7z/zJgbMOHL7oSN9hun4ZoGOn1ty8dRb/2+eZMk3Xb76vT/63z3Pe86imPjVqVA9vHxe8fVy4fNVVqz7dCbyEz/VTePu44Ol1QidN67aN+NNzOzu9djDg+/464XWb1GGj2++ceuRKq24ttcJGzx3F1rNb2H5+K98vGafXHj//cwTcucDUD9iza/cGAu5c4MLFYxp72rVvidflk1y7fgqvyydp06aZJk6fPrZcvXaKG75n+HFZZtuwbYcWXLzmjLevG+MnjdKjy5BNf/6Kt68bzh77KFdeXR569bXlzMXDml9Ewm1q1amhFXfH3g2cvXxMJ83m7Zpwwns/zj4H9bYdGja14oD7Tm5GXqJjtrbDbpetHL3oyKHzu3NsO/wrSE///L+PIIRQAhuBrkAtYKAQolY2sfnAQUmSGgBfA5tyMkvuGPwfQaFQsG7dMux6DKV+/XYMGGBPzS+ra8mMHPk1ySnPqFWrJevXb2P5T3MBePv2LxYv+YVZs/U/XPTpmrtiGuMGTaVn64F07dWJKl9U0pKJiYpl/qQfOXXMQ+v82zdvmffDUnq3Gcy4gVOYuXQyRYsV0atHKASNlo/Ac/Aq3NrOpKJ9M4pV193L3KBwAb4Y1ZmEm5l7gqvepnL7l0P4L92Xoz1CoWDI0tGsGfET8ztNoUmPllhU097XPiLwEUvtZrGo6zR8T/nQb06mQ3v39h2Lu81gcbcZbBjzc476PkbPbp3447fcdc4+ikJByRmTSJg8m9ivR1LQpj0GlSvqiL0560n80LHEDx3L65NuABjVrY1RvTrEDR5N3KBRGNWqgXHD+nrVCIWCkT+OZdXwH5nRcSLNe7TEsrp23oXfe8j87tOZ3WUK192uMHCOugGXHJ/Mot6zmdttKgvsZ9FjXG9KmJTMZoaCFb8uYFDfsbRuYkevvrZ8UaOqlsygoX1JSXlGs4Zd2LJpN/MXTwdAqVSycesqZk5dTJtmdvTuPpzU1DQA3E970rXDgA9knYKxy77jx+GLmdhhPC17tKZc9fJaMg/vPWS67VSmdJ7IFdfLDJs7UhN2fMtR1k7R39hUKBSs/m0xfXt/w1fWnenTz44aX1bTkhk2vB8pKc9oUL89mzbuZMmP6s5mUGAobVv1pFVzO/r0HMna9ctQKpUArFy1kLMel2hi3YW0tDQG9h9Lvfrt+HpAT2rW1PYD34wcSEryM2rWasm69dtYvnweADVrVmdAf3vqW7Wne/fBbFi/HIUi8xEw8YfRBAWHaaW1b/8xrKw6oFKl4+19jQ0b/qR//x58mc33jBgxgJSUZ9Su3ZoNG7azbNkcQO17lixZzezZP2nJv3z5iiZNump+ERFReLh66uTlgp9nMnbgJOxaDsC2d2eqflFZSyY6KpY5E5fietRd517s2OjIrPGLdG9SNhQKBdN+msTUIbMZ2G4EnXp2oFJ17boUGxXHj1N+xuP4OZ34f719x3CbMQy3GcPMkfN10l63bhk97IdR36o9A/rb6+TdyBFfk5KSQq3arVi/YTs/Lcv020uW/Mrs2fr9hb19F16+eqWl63PUpc2/76DVV7Z0bN2bxk0a0KJ9Uy2ds1dMY8KgafRpPZguvTrqeVbEsWjST5zO9qx4GpfICLvv+LrjCIZ2HcPIH4ZQ1rSMloy6Pi2hT6+RNG7Umb5661N/UlKeY1WvPRt/36GpT4GBobRpaU/LZt3p3XME6zZk1icA266DaNmsO21b2evonLBsPPOGzWdM+7G0tW9Lhera33aJj3rKr1NXc/74Ba3ztRrVpLZ1Lb6zGcfYjt/xRf0vqNe0nlbav61ZSu+eI7BuaEO/fj34Mps9w0f0JyXlGfXrtmPjhj81Df3ExCT69R1Nk6+68u2Y6Wz7U+2DSpUqwbLlc+huO5jG1p0xMSlD27bNUSgULFs1n6H9x9GuWQ/s+3Sjeo0qWrq+HtKbZynPaWndjW2b9zB3sbrjd+ywK53b9KVzm75M+m4OTyKiCLwboonXtXtHXr/S/QaNuu0wne8HTaNX60F6y0NsVCwLJi3T23aY/8NSercZwvcDpzJj6aQPth1kNHwF3Jck6aEkSe+AA4B9NhkJeP+Rk+JAdE6J/p/pGAghtr/vCQkh5uZRmiOEEL/nRVof0bFdTw/uk2nc2IoHD8J59CiC1NRUDh48gV2WNyAAdnY27NlzCIAjR11p1079JuP16zdcuXKDt29z98G0Og1qEfEokqiIaNJS0zh9/CztOmu/JYt+EktY0APSs/VoHz98QsSjSACexiWQlJBMydIl9Oop1aAqL8PjeBXxlPRUFREnrlKucyMduXoz+xK0yQXVX+8051Rv/iLheiiqv1JztKeKVTXiH8fy9Ek8qtQ0rjlfxsqmsZZMsM893r1Vp//wVhglzUrnmO7fwdqqLsWLFf3H6RjV+pK0yChU0TGQlsYbj/MUbN08d5ElCWFsBIYGCENDhIEBqqRkvaLVrKoTFx5D/JM4VKlp+Dh706jTV1oygT53NXkXdiuUUubqvFOlppH2Tt24MDQyRCh0P8nVoFE9Hj2MIOJxJKmpqRw/4kbnbtpvfjt3a8/B/eq3ei4nztCyjbph0rZ9CwLvhmgeWMnJKZry6OcbQHzcU702VbeqTkx4DHERcaSlpuHtfImvbJpoydz1ucO7jPoSeiuE0uaZ5eHO5du8ean/oz6NrOvz8OFjwsOfkJqaytHDLtjadtSS6WbbkX17jwJw/Ngp2rRVv/l78+YtKpUKgAIFjJEy5q8WLVqEFi0as3vXQXX6D8K5cyeY1NRUnA6ewM5OeyRGyw8ccaV9hh+ws+uM08ETvHv3jvDwJzx4EM5XjRsAYGlpTteuHdixY79WWqdPn9f4Hk/PK5ibm3DokLNe3+PoeBiAo0fdaNeuBZDpe/76663e/AKoWrUSJial8b16S+t8vYa1iXgUSeTjaFJT03A75k77Ltn9UAyhgfd1/BDAVa8bvHqZ8wf0ajX4ksjwaKIjYkhLTePsifO07txCSyY2Mo4HQQ/16vkYOn770En9fluTd646eff2L12/XbhwISZNGsOKFes15z5HXXrz5i2Xva4DkJqayp3bgZiYZ46e1WlQkydZnhVnjp+jbedWWjpjNM8K7fnYaalppL5T+28jY0OE0PUP1tnq05HDLth276QlY9u9I/v3HgHU9altW7Uf1KpPxsa5ng5ew6oG0eExxEbEkpaaxsWTF2lu00xLJi4yjkfBjzR19D2SBEbGRhgYGWBoZIiBoZLkhEzfam1dn4cPMu05fNhZ1x7bTux1VNtzLIs9twMCiY2JB9SdHmNjY4yMjKhUuQL3wx6RkKD+SNuFC5ex79kFq0Z1CX/0vjykceLoKWy6apcHm27tOXRAXR5cT7jTsrW2HwSw79ONE0dOaY4LFS7ImO+HsW71Fh3ZOg1qaZWH08fP6pSHvGg7/GvIhxEDIcRYIYRvlt/YLFdgCTzJchyZcS4ri4EhQohIwA34ISez/s90DCRJGi1J0vvPiuZJxyA/yHbdfxtLC3Min2R+CTIqKhYLS/NsMmZERqplVCoVz54/p3Rp7Te0ucHUvCxx0fGa47iYeK2HQW6p06AWhoaGPAmP0hteyKwUr6MTNcevY5IoaK59vSXrVKSQRWmiz97KHj3XlDAtRVJ0guY4OSaRkqYf/npnq/7tueOZqc/Q2IiFJ39m3rHlNMjWofhfoTQpgyou8x6p4hNQltW9RwXbtcLEcRulVixCaaIOf3c3kL9u+mPhehhzt0O8vXqDtPAIvXpKmpUiMSYz75JiEin1kU5TuwEdCfD00xyXMi/NytNr2HB1G85/HCMlXrsDYm5uQnRUrOY4JjoOc3PTbDKmREdllusXz19QqlQJqlSrhATsP7IN94tHGD9Rd6hcH6XMSpOQpTwkxiRS2vTDNnUc0Am/CzdzlbaFhSlRkdr11Nwimz0WZhoZlUrF82cvKJVRTxtZ1+fqjVNcuebGlEkLUKlUVKpUnoSEJDb9sYo/d6yhQoVyFCpUMCP9GCwtzLSvwdKMJ5HRmvSfPVP7AbV/yHxZFBUVg4WlOu7q1UuYM2eZ3oavhYUZUVGxDBrUG3f3i+p42WyyyJK2SqXi+fMXufY9AwbYc+iQs855E7OyxEbFaY7jYuIx/Rt+KCfKmpUhPou/i495SlmzMh+JoY2RsRE73P5gm/NGnQ6FhUXmvYAP3K+/kXeLF81g7dptvHmT2UH93HWpWPGi2HRpx3WvzLpgoudZUfYT7pGphQlO53dx6uYxHDbu5Wlcgla4eZZnGkB0VAwW2W2yMNV67j1/nlmfrK3rc+3GaXyun2LyxPmajoIkSRw/uYuL3icYMfJrrfTKmJXmaXTmS4WnMQmUzuWLoiC/IPx9Ajjgu48DN/fhe/EmT+5nttssLMyIjMr2HNcpD6YaGfVzXLc89OzZldsB93j37h0PH4TzRY2qVKhgiVKpxM6uE5blLDA3NyEmS3mIjY7D3NxEKx2zLDLqvHtJyVLajXG7Xl04cdRNczxj7g9s3biLN691O/sm5mWJjc6ss/ExT/9Wna3ToOZH2w7/PyFJ0lZJkqyz/LZmCdbtTatHCLIyEHCQJKkc0A3YI4T4aNv/X9kxEEIUFkK4CiEChBB3hRADhBCeQghrIcRKoKAQwl8IsTdDfogQ4nrGuS0Z864+lPZIIUSoEOIi0CLL+YpCiHMZizPOCSEqZJx3EEJszli88VAI0UYIsUMIESSEcMgSf3NGb+6eEGJJlvOeQgjrjP9fCiF+yrDrqhBC28OpZTS9w3TVqyzndW3J/rZC3xuX7DK5Ig/SKWNSmuUbFrJw8rIPx9VbpLPICkGDxUO4tWTvJ+nWUfMJ9jTt2YpK9apyemvmvNMZzb9jaY9ZbJ24loELR1K2gs5t+x+gt0BoHb718iGm5yDih4zhr+t+lFykHpJWlrPAoFIFYuz6E9O9P8bWDTCyqqebHiD06PlQ3rXo1YbKdavisuW45lxSTCKzu0xhSutxtO7TjmJlimunr+/ekJtyDQZKJU2aNmT8mBnYdxlM1+4dadm6qY6sjk2fUB7a9GpL1XrVOL7laI7pfuxatWV0473Xf9M3gKaNu9KuTS+mTvsOY2MjDAwMqG9Vmz+372Xhgp9JS0vTmmudOz/wYbu7devI0/gE/G7d+aBNzZpZ4+19ncuXr3+Cztz5jH79enDw4Em9evXZkdf8U7/Z66sBfNPtOxaNX8bkJROwrJg5bz83aefGt2elXr1aVK1akZMnT2dL5/PVJaVSyR/bf2X7FkeiIqKzJqjv4j947dmJi45nQPvh2DcbgF3/rpQqo90AztVz7yO+0Nc3gCaNu9C2dU+mTR+nWYNk06EfrVv0oE+vbxjz7VDqNqnzUaW5LQ8WlcypUK0Cg74awsDGg7FqbvGPFA4AACAASURBVKWVdu7Kw8dlatasztJls5j4g3qKYErKcyZPWsCuPb/jfvYgjx9HoUpLy5UdOelq0Kgub9+8ISRIPY23Vp0aVKpcgdOuulPq1Onpnvs7bYefNixk4eSf/l77JT+R0j//7+NEAlnnwZZDd6rQKOAggCRJPkAB4KNvPv6VHQOgCxAtSVJ9SZLqABoPKEnSbOCNJElWkiQNFkLUBAYALSRJsgJUwGB9iQohzIElqDsEnVAv1njP78BuSZLqAXuB9VnCSgLtgSmAM7AGqA3UFUJYZcjMkyTJGqgHtBFC6GtpFQauSpJUH7gEjMkukLV3qFAW1pyPjIqhXPnMEQJLSzNiomO14kZGxVCunFpGqVRSvFgxkpJS9GXFR4mLjsfUIvPNgqm5CU9jEz4SQ5vCRQqx0XE1G37eym2/ex+Uex2TRCGLzDcxhcxL8SY283oNixSgxJflaX9kPnbX1lKmYTVaOUzTLEDOLcmxiZSyyKwHJc1L67y5BqjVoi7dJ/Rh/eiVmikwgEb26ZN4gq/eo0LtT9P/OVDFP0VpmnmPlCZlUCVo36P0588hVT1U/+qEK0YZc5sLtm3Fu7uBSG/eIr15y1uf6xjVqalXT1JsIqXNM/OulHlpkuOSdOTqtKhHzwl9WT16hVbevSclPpnI0Ai+/Ep7Vl10dJzmrTWo3/69Hy7PlMkcHVMqlRQtVpTk5BSio+PwuXyDpKQU3rx5yzmPS9Srn/OsvcSYBMpkKQ+lzUuTFK9rU72W9ek7oT8rRi3Ta5M+oqJisSynXU9jY+K0ZKKzyCiVSooVL0pytnoaGvKAV6/fUKtWDaKiYoiKiuWmbwBRUbG8fv2G+vVrZ6RvTnS29KMiYyhfzkKTfvHixUhKSs7wD5mNVktLc2Ki42je3Jru3W0IC73KXsdNtGvXgl0Ome6vY8fWlCxZnJkzl2bGy3aPorKkrVQqKVasaK58T926NTEwUHJLT6ckLiYeM8vMTripuQnxsfqnh/0T4mOeYpLF35mYlyUhLvEjMbR5LxsdEYOfjz9f1MmcMx4VlXkv4AP3Kyr2k/KuaZNGNGhQj5CQK5w/d5Tq1Svj7n7ws9alX9ct4eHDx2zbvFsrvfh/+Kx4z9O4BB6EPKJhU+21TtFRsZpnGoCFpTkxsbo2ZX3u6cu/0JAHvHr1mlq11AtoYzPSSHiaiMtJd2pYZS6sTYhJoKxF5lvusuZlSNLj8/TRonMLgm8F8/b1W96+fsuNCzf4ssGXmvCoqBjKWWZ7jusrD5ZZn+OZ9lhYmrHvwBbGjp7Go0eZo7yn3M7Rrk0vOrTrQ1jYQ+7fD1ePGGUpD2YWpsRmqz9ZZdR5V4SU5Gea8B69u3I8yzSiRo2tqFu/Fj7+Zzh2ajdVqlZi+9HM2dhx0U8xyzKaaGJelvhPbDv87vgrv/+8lTsfaTvIaLgBVBdCVBZCGKFeXJz9LUsE0AEgo71cAPioI/23dgzuAB2FED8LIVpJkvTsI7IdgEbADSGEf8ZxlQ/INgE8JUl6mrFQwylLWDPg/UrWPUDWrQacJXXX9Q4QJ0nSHUmS0oF7QKUMmf5CCD/gFupOg74WyjvAJeP/m1ni5oivbwDVqlWmUqXyGBoa0r+/PS4u2ot3XFw8GDq0HwB9etvi6Xk5t8lrcc8/iIpVymNZwRwDQwO69OyIp7tXruIaGBqwdufPOB86hYfz+Y/KJvk/pGhlMwqXL4vCUEkF+6ZEumcOU6e+eMPROt/h3GQyzk0mk+B3H68Rq0m6/eiT7HkUcB/TSuaUKWeC0tCAJnYt8Pe4oSVToXZlhi3/lvWjV/Ii8bnmfKFihTEwUn/uo0jJolRv9CUxYZGfpP9z8C4oGIPylijNzcDAgIKd2vPmko+WjKJ05nSpAq2ak5oxXUgVG4dxg/qgVIBSiXGD+h+cSvQgIAyzyuaULa/Ou2Z2LbmZLe8q1q7MqBXjWD1qOc8TM6tqKbPSGGa8oStcrDBfWNck5oH20LC/3x2qVK1IhYqWGBoa0rNPN9xPaS/ocz91gf4D1euputt35vKlqwB4nvOmZu0aFCxYAKVSSbMWjQkNeZBj3oUFhGFe2QKT8qYYGBrQ0q41Nzyua8lUrl2FcSvGs3zUjzxL/Jj70cbv5m2qVq1ExYrlMDQ0pHff7ri5ab9dc3M7x6DB6t2devbqyqWL6vtWsWI5zeLI8uUtqF69Mo8jIomPTyAqKoZq1Svjd/M2VapWIiY6DkNDQwb0t8fFRXvhrYuLe6Yf6GPLhQw/4OLizoD+9up5yZXKU61aZa7fuMX8+SupXMWa6l80ZfCQ77lw4TLDR0wE1AuZa9aszuvXbzQ29etnp9f3DBmi3t2pd+9ueHpeyVV+9e9vr3e0AODOrcAMP2SBoaEB3XrZcOFM7vzQpxDkH0z5ypaYlzfDwNCAjvbt8XLP3fUXLV4EQyNDAIqXLEa9xnV4FPpYE67225Uy/Xa/Hvr9tibvcvbbW7ftoXIVa2rUaE77Dr0JC3uEjU3/z1aXZs2bRNFiRVkwe4XOtdzzD6ZClXJYZDwrOvfsgKe7d67yzsS8LMYFjDLysShWjesSfl/bD93MKO/vy16fvt1xcz2rJePmeo6Bg/sA6vp08UP16YsqPI6IpFChghQpon7pVqhQQdp3aEl4SLgmvZCAECwrWWCW4R/a9GiDj8fVXNkUHx1P3SZ1USgVKA2U1GtaV2sq0c2bt6laLdOevn3tdO1xO8vgIWp7emWxp3jxohw5soPFC1dx9ar21MayZdUv2EqUKMaYsUPY5eBEgN9dKlepQPkKlhgaGmDfuysep7XLg8epC/T7Wl0ebO1tuOx1TRMmhKC7vQ0nj2Z2DPbsdMK6dnuaWXWmV9dhPHwQzujembva3fMPokKVclpth4u5LA8Ghgas2bkyo+1wIecI/wKkdOmz/z6qX5LSgAnAGSAI9e5D94QQS4UQPTLEpgFjhBABwH5ghJTDUMy/8gNnkiSFCiEaoZ4PtUIIobvlRCYC2CVJ0pzcJv835N6v/krP8v/7YwMhRGVgOtBYkqTkjClGBfSkmZrlhqj4hPxXqVRMnrwAV5e9KJQKdjk4ERgUyqKF07npF4CLiwc7dx7AYec6AgO9SU5KYcjQzK3xQkN8KFasKEZGhvSw64yt7SCdHUiy6lo+dzWb969FqVRwfL8LD0Ie8f3MMQT6B+Hp7k1tq5qs3bGSYiWK0qZTS8bNGE3vNoPp3KMDDZtaUbxkMXoMUG+PuWDSMkLu6eqSVOn4znOg7b5ZCKWChwcu8jw0iroz+pAU8Igodz+dOFmxu7YWwyIFURgZUK6zNRcGruR5mO6cxHRVOo4LtzN193wUSgXeB88THRZJzykDCL/zAP+zvvSfMxTjQgX4ftM0ABKjEtgw5mfMq5Vj+PKxSJKEEAK3zceIvv/3OwYzFq3kxq3bpKQ8p0PPIXw/aih97PRv4/lRVOmk/LqBMut/RiiUvHI+RdqjcIqNHcG7oFDeel2hyIDeFGzVHEmlIv35c5KXqndUenP+EsbWDTDd+ycg8dbnBm+9ffSqSVel47BwG7N3L0KhVOB58BxRYU/oO3UgD2/fx+/sDQbPHU6BQgWYuGkGAInRT1k9egUW1coxZP4ITd65bj3OkxDtB79KpWLujGXsP7IdpVLBfsejhATfZ+bcH/C/dRf3UxfYt+cwv2/5GR+/06QkP+Pbb9T36Nmz52zZ6MDp84eQJIlzHpc4634RgAVLptOrry0FCxXE794FLh08j9Oa/Rqbti34g0V7lqBQKjjndJYnoREMnDqY+3fCuOFxneHzRlKgUAFmbFZPv3oa/ZQVo9S7w/x0eCWWVctRoHABtl3bycYZ6/G/dEtjz/RpSzh63AGlUoHjnsMEB4Uxd/5kbvnd4ZTbOfbsOsjW7au5FXCe5OQUvhkxCYCmzayZMu1bUlPTkNLTmTZlEUmJ6tGqmdOWsP3PNRgaGRIW+pDWbZtx57YnDrucCAwMZdGi6dy8qfYDO3YewMFhPUGB3iQnpzB4iNoPBAaGcuiwM7cDLpCmUjFx0rwcF9Nu3LiSiIgo0tPTCQg4z6tXb1i3bitBQaEsXDiVmzfv4OrqgYODEzt2rOXevUskJaUwbFhmYyEk5DJFi6p9j51dZ7p3H0Jwhu/p27c79vb6txtWqVQsm/0L253Wo1AqOLrPmfshD/lh1lju+gdx4YwXdaxqssFhFcWKF6OdTSt+mDkWu9bqOeN7Tm6lSrWKFCpckAv+zsyf8hOXL+g28FSqdFbPX8/afatQKBS4OJ3iUWg4Y6aPJCggBG+PK9SsX4OVf/5I0eJFaNmpGaOnjWRw+5FUql6RWSunki5JKIRgz+/7CQ97rGXD5MkLcHF2RKlU4rDLKSPvpuF38zYurh7sdDjAzh1rCbznRVJSCkOHZW5BGxJyhWJZ8s62+2BN3unLr7yuS+YWpkyZ8R2hIQ/wuKReEHt05wmO7XPW6Px57ho27f8NhVLJif0uPAx5xLiZown0D+aiuze1rL7ktx0rKFaiKK07teC7GaPp22YIlatXYuriCe/nubF7837uBz/UsWnGtMUcO7ELpVLBnt2HCA4KY978yfhl1Kfdu5zYuv03/G+fJzn5GSOHqzu1zZpbM2Xqd6SmpZGens7UyQtJSkymUqXy7D3wB6CeQnXo4El8PTMb2umqdH5fsInljj+hUCo44+TO49DHDJs2lNDbYVz1uMoX9b9g0bYFFC1elKYdmzB06lDGdvwWL1dvrJpbsdXjDyRJwvfiTa6evaZlz7Spizh+crfGnqCgMOYvmIKf3x3cXM+yy8GJ7X+uIeDOBZKTnzFimHqt6LffDadK1YrMmvMDs+aoz9nbDePp00RW/bKQunXVo74rV6zn/v1HlChQmAUzl7P38BYUSiVOe48RGvyA6XPGE3DrHh6nPTngeJR1f6zA29eNlORnfD96huZamza3JiY6jojHuX/eqVQqVsz9jc3716BQKrO0HUZzL6M81LaqyZqM8tCmU0u+nzGK3m2G6G07LJz0k962g0wmkiS5oV5UnPXcwiz/B5Jl2nxuEP/GOVxCCAsgSZKkt0KInsAIoAQwXZIkXyFEMmAiSVJqxo4/J1BPJYoXQpQCikqS9FhPuubAVaAh8Bw4DwRIkjRBCHESOCRJ0h4hxAjAXpKkXhmNfBdJkg4LISpl/F8nIz0H1CMAYcBuoAFQFrgNzJIkyUEI4Znlul9KklQkI25foLskSSM+lA9GxuXy5eZ8WbJ8zkJ5xBzFhwZz8hYPo9ztwPRP2eK7Kl/0AMTZ6u5L/jmYGVs8Z6E84vyz4HzR06xYtZyF8oDzSf94n4Fc8/rdh3f6yUuUig8u2cpTKhczy1kojyhhWDhnoTzAL/F+zkJ5RMkC+bO1o3mBD2/ckJc8eBGTs1Ae0bTUF/mi50piSM5CeUSJAvlTxksbFctZKI8IiL2ib2Xi/4zXf0z67G20Qt+ty3eb/5UjBkBd4BchRDqQCowDfs0SvhW4LYTwy1hnMB9wz1hpnQqMB3Q6BpIkxQghFgM+QAzgB7x/6k0EdgghZqCefzUye/wPIUlSgBDiFuqpRQ+BvzeHR0ZGRkZGRkZGRuZ/xL+yYyBJ0hnUc6ay0jZL+CxgVpZjJ7TXC3ws7Z3ATj3nw1EvMM5+fkQ2mTofCBuBHiRJynrdRbL8fxg4nJtrlpGRkZGRkZGR+ReR865B/yf5ty4+lpGRkZGRkZGRkZHJR/6VIwZ5gRDiGmCc7fRQSZL0b9YtIyMjIyMjIyMjkxty2DXo/yr/2Y6BJEm63/aWkZGRkZGRkZGRkdHLf7ZjICMjIyMjIyMjI/NZyGG75/+ryB2DfzH6Plf+OQh/EZezUB7RwLJkzkJ5wOvX+bOlXn5tIQpg6ro9X/SUsc7tJ0H+OQb5tBVmSUX2WYWfh/KFy+YslEcEv3uSs1AeYKTMn8fEw+f5tz1l8zJf5iyUB6jyseGQ+Pp5zkJ5QEmjovmi550qd18bzwviUvMn7yoWNclZKI9ITVfli540KX/0yOQfcsdARkZGRkZGRkZG5lP4j44YyLsSycjIyMjIyMjIyMjIIwYyMjIyMjIyMjIyn4Qk70okIyMjIyMjIyMjIyNPJZKRkZGRkZGRkZGR+a8ijxjIyMjIyMjIyMjIfAr/0Q+cySMGMjIyMjIyMjIyMjJyx+Dfjk2ntty57UngPS+mT/9eJ9zIyAjHPZsIvOeF16WTVKxYDoBSpUpw5owTiQnBrF3zo1Yc55N7uHH9DLf8zvL7huUoFOpi0LFTa27eOov/7fNMmfadXl07d63H//Z5znsepUIFSwAaNaqHt48L3j4uXL7qSnc7G614CoUCryvOHDysuw9/4VaNqHx6K1U8tlNqbD+d8OK9OlLt6n4qndhApRMbKN6vs3bahQtS1Ws3pgvHfSwbsWxbjz4Xf6Gf92rqjbfTCf9ySHt6nV1BzzM/YXt0ASWqW6jTN1TSavVYdZj7T5g1q/lRPQDGTRtjenAXZof3UHTYQJ3wQradMT99FJM9WzHZs5VCPbpl2jthLKb7d2B6YCfFp07IUdeHmL/8N1rbfk3PIbr38VOp2aY+886tYYHnOjqOs9cJbzfKlrkeq5l1ahXj986npGUZTViP2YOZ4/4rc8/+Rp9FI/Sm37ZDCy5ec8bb143xk0bphBsZGbLpz1/x9nXD2WMf5cqr702vvracuXhY84tIuE2tOjUAcDz0B+6XjnDuynFWrF6IUGi7ujptrFh+bh0rPDfQbVxPHZ02o7qzzGMNS06tZvreRZTOYtP2B04sdvuFxW6/8MO2WTnmX4t2TXG+7ITb1UOM+mGoTnijplYc9NiFf5Q3nbq30wr7Y/8aroR6sNHxV530ggO9mTljvJ78MmLf3s0EB3pzxdtZ4xMAZs2cQHCgN/fuXsKmUxsAypWz4Kz7Ie7c9iTA/zw/TMi8B/v2bsbbxwX/OxdITAnhaVJwnvgGY2MjLlw8xuWrrly7cZq58yZr0vocPs/Q0JBNG1dy985FbgdcoHW3llrhjdtas+viDhy9HRg4foCOznpN6rLl1CbOhp+mtW0rzXmr5vXZduYPze/MfVdadG6uSS8/7tH5s4d5+fwhL188JD7uHr433HV07d27maBAby5n0zVz5gSCAr25e/cSnTJ0AYSFXuWW31l8b7hz1cdNc37x4hkc99zL0fOObD+4nrKmZWjZriluVw5x+toRRv8wTMdW66YNOHJ2N3eir2DTvb1W2NYD67gWdo7Njr/pxAPo1KkNt29f4N69Sx8sC3v2bOTevUtcunQiW1k4QEJCEGvWLNWKY2hoyMaNK7lzx5OAgPP07NlVJ93m7Zpwwns/zj4H+WaCbp1t2NSKA+47uRl5iY5Z6myN2tXZ7bKVoxcdOXR+N53tO+i16z0t2zXF5fJBTl09rDfvGjW14pDHLgKiLuvk3Zb9a/EJPctGx9UfTL9V+2ac9jmCx/VjjJ04XCfc0MiQtduW43H9GIdOO2BZ3lx93tCAFesX4nzxACcv7OOr5o00cbr17MRJz/24ejkxY+HEfLfpX4WU/vl//wP+VVOJhBDbgd8kSQoUQsyVJGl5Pui0AiwkSXLLUTifUSgUrFu3jG62g4iMjOHKZRdcXDwIDg7TyIwc8TUpKSnUqt2Kfv168NOyuQwZ+j1v3/7FkiW/UrtWDWrXrqGV7qDB43jx4iUAB/ZvoVfvbhw76sbq35ZgbzeMqKhYPL2O4+Z6lpDg+5p4w4b3JyXlOVb12tOnb3eW/DiLkcMnEhgYSpuW9qhUKkzNynLlqiun3M6hUqk/fDJu/EhCQx5QtGiR7AZiuuh7noycR2psApWOrOXluau8e6D94aYXbpeIW7pZbx6VmTyM19fvfjQfhULQfNlwTg9ayauYJHq4LiXC/SYpYdEamQfHfQh2PA9AhU4NabJoCGeGrKLGILXTP9ZxDgVKF6PznhmcsF344d0IFApKzpjE0x9moIp/ionDZt54XSHt0WMtsTdnPUn5db3WOaO6tTGqV4e4weqPppXdug7jhvX5yy/go/bpo2e3Tgzq04O5P/6as/BHEApBv6XfsHHIT6TEJjL95AruevgSez9KIxMZGM4vdnNIffuOlkM6YT9nMA4T1lG54RdUsa7Byi4zAJh8eCnVmtbi/tVATVyFQsGyVfMZ1HsMMdGxuJ5zwv30BcJCHmpkvh7Sm2cpz2lp3Y0evbsyd/FUvh81nWOHXTl22BWAL2tW58+96wm8GwLAd99M4+WLVwBs3bWGxrbNuO58OcMmBUOWjmb1kKUkxSax8ORK/D18ib4fqdEZEfiIpXazePf2HW2H2NBvzlD+mLAGgHdv37G424xc5Z9CoWD+yumM6T+R2Oh4nM7s5MIZLx6GhmtkYqLimD/pR0aMG6QTf+emvRQoWID+w3rqpHfxnh9XfdxwdnEnKCjTJ3wzciDJyc/4slZL+vfvwYrl8xg0eBw1a1anf3976lm1x8LClDOnDlCzdivS0tKYMXMJt/zvUqRIYa5fO83Zc5cICgpj0OBxFDEuyK2Ac+zbe5ToqFj69rP7x77hr7/e0b3bYF69eo2BgQHuZw/ievosvr4Bn8XnzZ79A/FPE6lTtw1CCDpXa6x1jyYt+4EZg2bxNCaBP1x/54q7D4/DIjQycVHx/Dz1FwZ8q/3ywv9KAGM6qztKRUsUxdHbAT+vW2xz/4MZg2ZxLMDrs96jkJAHWFqaU7d+W6IiY3gcfhNv72ta1/jNyIGkJD+jZoau5cvnMThD14D+9tTP0HX61AFq1W5FesaCyo6d+pGYmKyV1urVm3Fcuw+AIaP7M37GaJq1/opR/SYQFx3PQfddXDjjxYPQR5o40VGxzJm4lG++H6JTvndsdKRAQWMGDOutE/b++WdrO5jIyBguX3bWKQsjRgwgJeUZtWu3pl8/O5Ytm8PQoeMzysJqatWqQe3aX+iUhadPE6hbty1CCEqVKkEZCmvpnbtiOt/2n0RcTDz7Tv+Jp7t2nY2NimXBpGUM/167zr5985b5Pywl4lEkZU3LsN99B1cuXOPF85d67Zu3cgZj+v9AXHQ8TmccdPIuJiqOeZN+ZMS4wbp5t8mRggUL0G9YL52w9+kvWjmLkf3GExsdxxH33Zw7fUkr/X6D7XmW8oJOX/XCtqcNMxb+wOQxc+k/VJ2mXZuvKVWmJNsPrKdPp2EUL1GMmYsm0avjEJITU/j598U0aWXNNS/ffLFJJn/4V40YSJI0WpKk962Gufmk1grolqPUP0QI8cmfeG3c2IoHD8J59CiC1NRUDh46iV22t/F2djbscTwMwNGjrrRr1wKA16/fcOXKDd7+9ZdOuu87BQYGBhgZGSJJEtbW9Xn48DHh4U9ITU3lyGEXbLt30opn270j+/ceAeD4sVO0bdscgDdv3mo6AQWMjbXazBYWZnTu0o5dDk4611Gg3he8exxN6pNYSE3jueslinRsluv8Ma5dDYMyJXjt7fdRubJWVXkeHseLiKekp6p4eOIqFWwaacmkvnyj+d+gkDFShhElqlsSffkeAG8Tn/Pu+WvK1K/8QV1Gtb4kLTIKVXQMpKXxxuM8BVs3z51BkoQwNgJDA4ShIcLAAFVScs7x9GBtVZfixf75F0orWlXj6eM4Ep/Eo0pV4ed8hbo2jbVkwnzukfr2HQDht8IoYVYaAAkJQ2NDDAwNMDAyRGmg5MXTZ1pxrRrVJfxRBBGPI0lNTePE0VPYdNV+i2TTrT2HDpwAwPWEOy1bN9G5Tvs+3Thx5JTm+H2nwMDAAENDQ839BKhiVY34x7E8fRKPKjWNa86XscpmU7DPPd5l2PTwVhglM2z6VOo2rEXEo0giH0eTlprGqeMetO/SWksm+kkMoYH3SdczX/Waly+vX77Wm15qaioHD56gh532KFoPOxv27DkEwJEjrrRv1zLjfGcOHjzBu3fvCA9/woMH4XzVuAGxsfHc8ld3rl++fEVwcBiWFmaa9N77hg4dW3HQ6USe+YZXr9R2GRoaYGBogCRJn83nDR8+gFWrfgdAkiSeJ2d+6fZLqxpEh0cTExFLWmoa50940sJGu87GRcbxMOiR3nv0nja2rbh+4QaVv6ykSe9z36OvGjfQyi9DQ0P+evdON7/06LKz64yTHl0f4/2zA6BgoYKUKl0yS3lMw+2Y+0fKt+7bz6teN3iVpXxnJXtZOHTIWW9ZcNSUBTedsvDXX2910h0+vD+rVm0E1GUhe+enToNaPHkUSVSEus6ePn6Wtp1baclEP4klLOiBjk2PHz4h4pH6BcPTuASSEpIpWbqEXvvqNlTr0eTdcQ/afSDvJD15d83L94N5B1CvYW0ehz/hyeMoUlPTcD3uTseubbRkOnRtwzEnFwBOO5+jWauvAKhWozI+l24AkJSQzItnL6hrVYvyFS0Jf/CY5MQUAK5cvI6NbeaIyee26V9HuvT5f/8D/mcdAyFEYSGEqxAiQAhxVwgxQAjhKYSwFkKsBAoKIfyFEHsz5IcIIa5nnNvysYa2EKKLEMIvI+1zGee+EkJcEULcyvhbQwhhBCwFBmSkOyDjunYIIW5kyNpnxC8khDgohLgthHASQlwTQlhnhA0UQtzJsOPnLNfxUgixVAhxDZgvhDiWJayTEOLox/LIwsKMJ5GZb7WjomK0HtjvZSIzZFQqFc+fv6B06ZI55r+LsyORT27x4uUrjh87hbmFGZGRMZrw6KgYLMxNteKYW5hqZN7rKpWhy9q6PtdunMbn+ikmT5yvaQysXLWAhfNW6n0oGJqWJi02QXOcFpuAoaluA6yoTQsqndyIxfq5GJhlTOkQAtPZo4n/+c8cbS1kXpJXMUma49exSRQ2182jmsM70s97NY3nfc3VhbsBSAqKoKJNQ4RSQZHyZSldtxJFLD7cSFSalEEVF685VsUnoCxbVkeuQxP1ZwAAIABJREFUYLtWmDhuo9SKRShN1OHv7gby101/LFwPY+52iLdXb5AWHqETNz8pYVqKlOhEzXFKTCLFTT9cvpr2b0egpz8A4X5hhPrc48cbW1h2fQtBlwKIexClJW9ubkJMVKzmODY6DnNzEy0Zsywy6nL3kpKltB+2dr26cOKo9qCf4+Et+Ide5NXLV/i6XdWyKSk6s9wlxyRS0rTUB21q1b89dzxvaY4NjY1YePJn5h1bToNsHYrsmJiVJTY6szzERcdjYqZbHnJL9vQio2KwyO4TLDP9hkql4tmz55QuXVLHn0RGxWBhqR23YsVyWNWvw7XrmfaaW5iRmppGfHwiDx6E55lvUCgUePu48CD8BhfOX+bGDf/P4vOKFy8GwOJFM7jq48a+vZspWSaz/JQxL0N8zFPN8dPYBMqYl9FJJyfa9WjLueMXdNL7nPcoazotWzYhOTmFAsbGudJlmSUfQZ3X73VJksQpt/1cu3qK0aO03+xOmjOO87ecsevTBU93b2Kj4jRhcTHxmJr//fKtdd36rs/C9IMyn1IWFi2ajo+PK3v3bsbERPtem5iXJTY606b4mKd/y6Y6DWpiaGjIk/AoveGmZibEZNETFx2P6T/wDTrpm5to3ZvY6HhMs/lWUzMTYjJkVCoVL56/pGSp4gTfDaND1zYolUrKVbCgdv2amFma8vjRE6pUr4RleXOUSiUdu7XFzNJUO73PaJNM/vC/HDHoAkRLklRfkqQ6wOn3AZIkzQbeSJJkJUnSYCFETWAA0EKSJCtABeiOQwFCiLLANqCPJEn1gfdjv8FAa0mSGgALgeWSJL3L+N8pQ5cTMA84L0lSY6Ad8IsQojDwPZAsSVI94EegUYY+C+BnoD3q0YfGQoj3k5YLA3clSWqCugNSM+P6AEYCO/Vc/1ghhK8QwleSdN98SdmmsAihmwfZZfTR3W4IFStZY2xkRJu2zXOVjkCvEAC+vgE0adyFtq17Mm36OIyNjejSpT0JTxPx9//AVB/9SrUOX1y4xoN2IwjvMZ7XV/wx/3kaACUG2/Lyoq9Wx+LD6OrRl0VBu85yqOU0biw/gNVE9S0MPXCRVzFJ2Lv9SNPFQ4i/GUZ6muqTdGVX9tbLh5ieg4gfMoa/rvtRctFsAJTlLDCoVIH/x95ZR1WVfg34OfcSioqKRdktBnYPYmAAwhjoGGOOo47j2N2dY45jja1jKwJKSIpioIAKAhYGqYQtwuV8f1y8cLmgOD9k4jvPWqzFPWe/e5/91jlvx9o6EGvjgG6zxuiYN8yHf1+RXNIor+zVzL4dlRpWx2v7GQDKVq6AYQ0T5rUaw9xWo6nVpj7VW+RYo5Gr/px5/NMyjZs24P27d0TcuacmM6jPjzSta4mOrg5129TPt77stLJvT5WG1XHd7qi6NrXNaBb1nM728ev5bt4wylWqkGvYPG3lKf158vPsuct8PmyxYnocPbKDSVPmq/UMCwJUrVqJ48fO5G3zC+sGgIyMDNq1tqFurTY0bdqQevVq59O/3EzlHataWnIqmhpzKeAarVr34MqVG4ye++Mnnz0/dWh2DMobUK1OVa75BuZLX0GlUXb5/v3suXzleoHYsuhgT4uW3bCxHcSYMUNp1y5rlG7D8t/p2NgWpxOutO+kOcJbUGc+/fW8/um8YGpqTEBAIK1bW3PlynVWrJiTQ6dmuC/ND2XLl2HppnnMm7A077C52fmfaocc6vPzTs+j2B4/dIa4mAROnt/HrCWTCbp2E0W6gpcvXjF/6grW71jOIacdylGV7O/Dr+zTPw0xI+Or//0d/J0Ng1tAZ0EQVgqC0F4UxRefkO2E8kP8miAIwZm/q+Uh2wrwE0XxIYAoih+7iksCxwRBuA2sA8zyCG8FzMi04wMUASoB7YDDmTpvAzcz5ZsDPqIoPhNFMR04CHwcO1MAJzLDiMB+YJAgCKWA1kDW3IdMRFHcLopiM1EUm8XGJlPR1Fh1z8TEiJjYeDX56Og4TDNl5HI5+volSEpKycM1dVJTU3F28cDaujMx0XGYmhqp7hmbGBEbl6AmHxOTJZOXrciI+7x585Z69WrTsnVTult34laYH7v3buQbi9YYrZ6ikk2Le541AgBoGZYlLSFJTV9GyivEtHQAUo66UqR+DQCKmtel9CAbqnvtptyMEejbd6LclKG5+vk2NoliRlk9wnqGBryNy3uKzgPHy1TuqpxqJCoyuLLwIKe7zub8iHXo6Ovx8mFcnmEVCc+QV8jqlZGXL4viuXrjJePlS0hLA+CNows6dWoqferQng+3wxDfvUd89573AVfRqf/5xc5fk5S4REplGyEpZVSGlwmacVerbQOsxvVi+8hVpH9QplfDri2ICrrLh7epfHibyh2fYKo0rqkWLjYmHqNsPaKGxhWIi3uWp4wy3xUnJTmruujZqzunT2gUJQBSUz/gfs6bxl2yevaT4xIxMM7Kd6WNypCSi0/12jbAZlxvNo5cofIJUMk+e5JA+OVQKpnlPbUsPjYBQ+Os/FDBuDzPcvj3JeTUZ2piRGzOOuFprKrekMvllCypT1JSMtHRsWr1iamJkap3T0tLi2NHdvDnn6c4fVo9LuPiEqhStRInM9dzFETdkJ0XL17hf+EKXa06aDxjQdR5iYnJvHnzFkdHZd/TiZPO1MqsRwCexT6jfLYe4XKGZUmMS9TQ8yksbS3wd72IIl2hoe9rptFHPXK5HHv77jx5HK0ZX3nYehodq4pHUMb1R1sfn/fZs0ROO56jeXNzDZ9dTrph1rCOeo+xUXkS/of8rfbcuT1fbEKeMn8lL5w86YK5eX01mfiYZxhmG5kob1SOhHx1QCkpVlyPzQfWsHnldm7dCM1TLj42AaNsdioYl/8iO58jLiZBLW0MjTXTJi42AaNMGblcTonMulWhULB87q/YWQ5k7PeTKaFfnKgHytFrb/cL9O02lH49hvPw3iMeP8haE/i1fZIoHP62hoEoipEoP/ZvAcsFQZj3CXEB2JvZq28uimJtURQXfEI2tybqYsA7c3TCFuUHf17he2ezVUkUxTvk2hZWyefFe1EUs3cv7wYGAd8BxzIbEnkSGBhCjRpVqFKlItra2jj07Ymzs4eajLOzB4MH9QGgVy9rfHwufkolxYrpYWio/LCQy+V069qRyMj7XL9+k2rVq1C5sina2tr07mPDWZfzamHPunjy3cDeANh/2x1f3wBAObQtlytndlWsaEzNWtV49PgpC+evpm6ttjSo9w3DhozHzzeA2KlZi2Hf34pEp4ox2qYVQFsLfetveO15Wc2mvFzWsHDxTi1VC5Njp6zmfoeh3O84jGcr/uDlaU+erdmTq8/PQh6gX9WQ4hXLIdOWU82uFY891Ncl6FfNqswqdjLnRebHv7yIDlpFlUPzxu3rI6ZnqC1azsmHO+FoVTRBbmQIWloU7dKRd34BajKyMlmNlCLt25CWOV1IERePbuNGIJeBXI5u40Z/+1SixyH3KVfFEAPTcsi15TSxbcMtj0A1GVOzKvRfNpIdI1fxOjFr7nZyzHNqtKyHTC5DpiWnesu6xGdb4AsQcuM2VatVomIlE7S1tbDr1R0PV281GY9z3vTtr9wNydrOiosXshZXCoKAjZ0VZ05mfczqFStK+QrKD3+5XE7HLt8Qm20K08OQe1SoYkRZ0/LItbVoaduWYI9rajYrmVXl+2U/snHkCl5l80lPvxhaOso9G4qXLkHNpnWIvavuU3ZuB92hUrWKmFQyQktbi+72XfB2u5Cn/OfIrk9bWxsHBzucnNV3oXFydmfwYOVAae/e1nhn1glOzu44ONiho6NDlSoVqVGjKlevKacM7di+ljvh91i/YbuGTX39EogZGWhraxVY3VCmrAElSyrXwBQpoksHy7ZERNz7KnUegIvLeSwslL3blpbtiMq2sDg8JAKTqiYYVjRES1uLjnYduOQRkJeqXOloZ4mno7eGvq+dRtcCg6lRoyoDB/QiMvI+3bp1xDmHLec8bDk7u9MvF1t6ekUpXly5GFdPryhdOlsQGqpc1F+jRlYj2LLrN9y5HUnlahUxqWSMtrYWPb61+p/yd3aUeaGqKi/07Wuba14YpMoLPfDxufRZvep5oa3aonCA0OA7VKpmqiqz3ew74+vun69n1tLWYt3uFTgdO4eHk/cnZdXLshY97Lvg7eaXLzv54VZQGFWqVsQ0M22s7a3wdFXX7+Xqx7f9bADoZtuJAH9lPVikqC5F9ZSfSG0sWqJQKFQLiA3KKt/J+iVLMGB4H44fzBpN/do+/eP4j64x+Nt2JcqcgpMkiuIBQRBeA0NziKQJgqAtimIa4Ak4CoKwThTFBEEQDIASoig+QpMA4DdBEKqKovhQEASDzFGDksDHr4Pstl4B2VdpugE/C4LwsyiKoiAIjUVRDAL8AQfAWxCEekCDTPkrwAZBEMoCySg/+jfl5rMoijGCIMQAc4AuuclkR6FQMGHCXJydDiCXy9mz9wh37kQyb95kbly/ibOLB7v3HGb3rvWEhV4gKSmFwd9nbY0XEXEJ/RIl0NHRxta2K9Y2A0lKSubE8V3o6uogl8vw8bnEHzsPoVAomDp5Aacc9yKXy9i/7xjhd+4ye84Ebty4xbmznuzbe4TtO38l+KYXyckvGDZEuVVZ6zbNmDhpNGnp6WRkZDBpwjySEvOxaFaRQfyi36n4xxKQy3hx3J0P9x5Tdvwg3t++y2uvKxh8b0fxji0RFQoUKa+InZH7tnafQlRkEDB3L90OTkOQyYg84ktKZDRNpvTmechDHnvcoN5QK4zbmZGRriD1xRv8Jm4DoGhZfboenA4ZGbyJS8b3l9x3R8ruU8qaTZTduBJBJueN0znSH0ahP2ooH+5E8v7CJYr360XR9m0QFQoyXr4keZFyWco7Lz90mzWmwsE/AJH3Add47/9lHygfmTp/BdeCbpKS8pJO9oMYO2IwvXMsgMwPGYoMjs/bxdh9s5DJZVw+6kPc3af0mNiXx7cecPv8dexmDkJHrwjDtkwEIDn6OTt+WE3w2cvUalOfGW5rQBS54xvMbU/1BplCoWDutGUcPL4NmVzOkYOniAy/z5SZPxESFIqHqw+HD5xkw9bl+AeeJSX5BWNHZu0I1KpNM2Jj4nn8KOvjXE9Pj10HN6Orq4NMLuOS3xUuHsz6WMpQZHBg3k4m7ZuDTC7D/6gXMXefYj+xH1G37hN8PhCHmYPR1SvC2C3KqWuJ0c/Z9MNKjGqYMmTZKERRRBAEzv5+Sm03o5woFAqWzVzDtsMbkMtlnPrTmfsRD/lp2g+EhoTj43aB+uZ1Wb97JfqlStDBqh0/Tf0Bewvlbid7HbdStUZl9IoV5XzQGeZNXKrSpyCDPXuPEBYWyYL5Uwi8HoKzswe7dh9m756NhIf5k5ycwoBBym0ew8IiOX7ciVsh3qQrFIz/ZTYZGRm0bdOcwYP6cPNWmGqry7lzV3DOVblL17e9erB379ECrRvM6tdh6/bVyOVyZDKBUyfOcvacJ0CB13nh4XeZPWcZu3ZtYM3qBTx/nsjv07eo5YeNczez6uByZDIZ5464ERX5iGFThhAREskljwBqN6rF4p0LKF6yOK27tGLYpO8Z1ukHACqYVqCccTlCAm5q6Fsipn/1NPplwhwOHNjCh9QPbNy0k7CwSObPn8L1bLb27NnInUxbA7PZOnbciZs5bFWoUI7jx5Rrt+Racg4fPo27uw8AS5fOpEGdOmSIGcQ8iWPB1BXUMavJziMbkcllnDzkxL2IB/w8fRS3g+/gnZm/N+1ZhX5JfSyt2vPztFHYftMfgP1ntlMtM397BzsxZ+JSLnpfVpWdCRPm4uS0H7lczl5VXpjE9eu3cHHxYM+eI+zatZ7QUD+SklL4/vusLZ4jIi5SIltesLEZRHj4XebMWc6uXetZvXo+z58nMWrUZPSy9ZEqFAqWz/qV3/9ch0wu53RmmR07bSShweH4uvtjZl6XdbuWo1+qBBZd2jF26gh6WQyia89ONGllTsnS+vTsp9zTZN4vS4kIVW98fLSzdOYath9Wxt2pP524H/GQcdNGERqSFXcbdq/KrBva89PUH7CzUG6Bvc9xm6pu8AxyYt7EJVz0uaKmf9HM1fxxdBNymZzjf57hXsQDxk//kdvBd/By8+PYQUdWb1mEx9VTvEh+ycRRyj1fypQ14I+jmxEzMoiPTWDq2Kx+2zlLp1DHTDny+9uanTzKNmLwtX2SKByEL507V2CGBaErsBrIANKAMcAaYIooioGZi3h7Ajcy1xn0A2aiHOVIA34SRfFyHrq7A8syZRNEUewiCEJrYC/wDPACBouiWCWzkeEGaAPLgTPAeqANytGAKFEUbTLXGewFagFBQH2gvyiKdwVBGJD5bAJwVhTFaZnP8VoURbU9OgVB6A9MEEWx1efiSLdIxUJJHF25dmGYAeCqSZ1CsXPxbd6LSQuSriZ5jx4UNBVcNM+B+BpMbjazUOwAnHyZ91B7QWKlXzj57uq7vBsJBU148pPPCxUAetq6nxcqAFIVaYViB6BN2cLJDxcSwj4vVEB8aui6IKlRyqRQ7Dx8mfeUzYKmdinTzwsVAOnip9anFSxpGYVjS1v2xRsu/mVC468UVjbPF2+WDPrq32jF5hwodJ//thEDURTdUH6QZ6dDtvvTgenZfh8BNPe8zF33OXLM3xdFMQDlR/1H5mZeT0K5TiA7P6LJe2CQKIrvBUGojnIU41GmjkPAoVyeo3jOayjXKuzIjx8SEhISEhISEhIShcU/6oCzfzh6KKcRaaPsnBmTuatRvhEE4TrwBpj8FZ5PQkJCQkJCQkKiMPib1gB8bf7VDYPM8wFyjnMPFkXxVkHbEkXxFdDsf9TR9PNSEhISEhISEhISEoXPv7phkHk+gISEhISEhISEhETh8TedM/C1+TvPMZCQkJCQkJCQkJCQ+Ifwrx4x+K9TWDtGdS3b4PNCBcTg1/nYxrQASEmL/7xQAeAZV6lQ7ACULaTdgtYGLi8UOwDBjX4oFDs/ZxTOjjcTtXPbb+DfzQfFJ49bKTAEBAYYtigUW40VeR1jU7CEFS2cnaMAMgrphNnnqZ86i7TgKF2k8MrSkzcFcyjb53j94V2h2IHcT4X+GhTTLpyy9I/kP7rGQBoxkJCQkJD42ymsRoGEhISERN5IIwYSEhISEhISEhISX4L431xjIDUMJCQkJCQkJCQkJL4EaSqRhISEhISEhISEhMR/FWnEQEJCQkJCQkJCQuILEKXtSiUkJCQkJCQkJCQk/qtIIwYSEhISEhISEhISX4K0xkDi78DKqgO3b/kSFubP1Ck/adzX0dHh4IEthIX543/BicqVTQEwMCiFu9tRkhIjWL9+iVqYRQuncf/eVZISI/K0a27RmA1eW9jkuxX7Mb017tuM7Mm685tZ47qBeYcWUdakHABV6lVl6amV/OqxiTWuG2hj0+6T/rXu0ILjFw5w8uIhhowbqHG/cctG7HfbScBjLzpaW2jcL1ZcD5frJ5i6dILGvfYdW+MWcILzV08zavxQjfs6Otqs37Gc81dPc9x1LyYVjQDQ1tZixcb5OPse4Yz3n7Ro01QVRltbi8VrZ+N++SSul07QvHsrDb0NLRqzxmszv/puwXZML437PUb2ZNX5jaxwXcesQwtVcVfWpBxLndew7OyvrPLYQKeBXfOOOKCuRSNme65jrs8GOo+x07hvOcKaWR5rmX5uFT8dnENpk7Kqez1nDGSm+xpmnf+V3vM14+ZLmLPsV76x7o/9oNH/kx6AFh2ac8BvD4f89zHwp/4a9xu1bMBO1614PXLHwvobtXvljcuz9tBK9vvsYp/3LgxNK+Rpp4RFY+p6b6Ge31YqjNXM3wZ9OlI/aB+1z62j9rl1lOnfRXWv+r75NLh1kGq75+Tbp32+uznov5cBufjUsGUDtp/7Hc8oNyys26uum7dpxE63rao/93tnade1jUpfeJg/06bmXiccOvg74WH+XPLPqhMApk8bR3iYP6G3/bDqklWedmxfS8zTEIKDPNV09e5tw40b53n7NoqIiEuEhvoxZcrYXG3u3/8boaF++Pk5qtVDbm6Hef78DuvWLVIL4+DQk8BAd65dc+PMmX0UL11CQ299C3OWeW5guc8meoyx17hvNcKGJR7rWHhuLVMOzqdMtjy+8/4RFpxdzYKzq/l5x3SNsNmp1KEhg3xWM/jCWpqOtdV8jkEd+c5jOf1dl9L7xFxK1zQGoJZ9G/q7LlX9jXu0j7L11M82sezUjouB57gc5MbPEzXP7dDR0Wb77l+5HOTGOc8jVKxkAkDFSiZExQXjeeEUnhdOsWrdAgCKFS+muuZ54RRhDwJYvFx5xknHTu0JCHTlapA74/OwtWP3Oq4GuePqeVTN1uO4ELwvnMb7wmlWr1uoCjNr7gSCQ32Iir6hulZYdiw7tePCNRcu3XBl3ISRudrZumstl2644nL+MKaVjFX36prVwsn9ED4BZ/C6eBpdXR0AtLW1Wb1+Af6BZ7lw1Rnrnsqy3alze67ccCMw+Dy/TBqViy0d/tiznsDg83h4HVf59BETUyMexwYzbvwI1bXg2974X3bG9+IZPH1PAgX/Ti9atAinT+/l1k0fgoM8Wbok67wbqy4duHXTh7DQC3mW2wP7txAWeoELfmdylNsjJD4PZ/26xWphnM7s59pVN4JunGfzpmXIZLKvEnf6JUuwZ/8mLl935XKgK81bmGvolfg6SCMG/2BkMhkbNiyhR48BPH0aS8AlF5yd3bkTflclM2xYf5JTXlCvXjsc+vZk2dJZDBw0lvfvU1mwcDVmZrUxM6ujptfZ5Txbft9DWOiFPO2OWPwjiwfOJykukeVn1hB4/ipP72Yd1vMw9CHTbSbx4f0HrAZ1Y/DMoawbt5rUd6lsmrieuKhYSpc3YKXLWoL9gnj78k2udqYtm8i4/pOIj33G3rPb8XPz5+HdRyqZuOh4Fk5YxqDRmh9UAKOnjeTG5eBcdS9YMYOhfccSFxPPCff9eLn6ci/yoUqmz0B7Xqa8pHMLe6ztrZg6bzwTfpiJw+BvAbCx6IdB2dL8cXgTvboMRhRFxkwcQdLzJKxa9UIQBCyN66nZFWQyhi0exfKBC0iMS2TJmVXcOH+V6LtPVTJRoQ+YYzOFD+8/0HlQV76b+T2bxq0lOSGZ+b1mkP4hHV29Iqxy38B1j6ukJGgeCifIBPouGs5vg5aSEpfIlDPLue0RSNy9aJXM07AoVtvOJO39B9oN6oLdzIHsGbeBqk1qUa1ZbVZ0mwrAhOOLqNGqHvcuh+Uax5/DvkcXBvTuyazFa/5S+I/IZDImLh3PpO+m8Sz2GdvPbsHfPYBH2fJDfHQCyyauov/ovhrhZ2+Yzv6Nhwi8cJ2iekXIyKs3Ryaj4pIfuTdwPmmxidR2WsMLj6u8v6t+GFWKkz9P523XCB6/7RSyorqU/UzD7aNPvyz5mSkDpvMs9hlbXX7jovslHt19rJJJiE5gxaRV9PvRQS1s8KUQRnZVNrZKlCrBQf+9XL8QxE73bUwZMJ3TIRe4HHAWJ2d37tzJqhOGD/uO5OQX1KnXDgeHnixfNpsBA8dQt25NHBzsaGjeEWPjCridO0xds/ZkZGSwb99RtmzZze7dG9SeITQ0nO++G83ly2eZPHk+bm4+XLzohLOzB+HZ6qGhQ/uRkvICM7Nv6NvXliVLZjJ48E+8f5/KwoVrqVevNmZmtVTycrmcNWsW0LhxJxITk1m6dBadhnTHcf1RlYwgkzFo0UjWDlpEUlwS886sINgjkJh7WWXpcdhDFtlO58P7D3QYZEXfmYPZOm4dAB/ef2BBj6mfTSNBJtBhyRBOD1jB69gk+jkv4oHHdZLvxqhkIk4HcPuAFwBVuzSh/bxBnBm8isjTl4g8fQmAMnVMsd45iedhWWkrk8lYsXYeDvbDiYmOx837GG5nvYiMuK+SGfB9H1JSXtKqcVfse/dg7sLJjBo2CYBHDx/Tqf23as/75vUbtWvuvidwcfJQ2eprP4yY6HjcvY/jmsPWwO/7kpLykhaNrbDv3YN5C6fww7CJAEQ9fIxle83Gl9s5b/7YfpArN9zUfCoMO8vWzKGf/UhiY+I5530E93Peana+G9ybFykvadOkG3a9ujNnwWRGD5+MXC5n8/aV/PzjDMJuR1C6dEnS0pQH9f0y5UeeP0uiXbMeCIJA6dIlkclkrFq7gF52Q4mJjsPT9wSuLl5ERNxT2RqUmU7NzDvTq7c1CxZNZcTQrA6pZStm4+nhp+FXT+vBJCUmq3z6Gu/0deu24et7CW1tbdxcD9O1qyXnz/spbVkrbV266KxRbocN7U9KSgr1zNrTt29Pli6ZxaDBYzPL7RrM6tXGzKy2mq0BA8fw6tVrAA7/uY1ve/Vg1tyJBR53y1fNwfO8H0MH/4y2tjZF9f6BB6lJIwYSX4ogCD0FQZiRx73XnwvfvLk59+9H8fDhY9LS0jh61BFbWys1GVtbK/bvPwbAiZMuWFoqe+jfvn3HpUvXeP8+VUPv1as3iItLyNNuDfOaxEXFkfAknvS0dC46XaBZF/XDh0IDbvHh/QcAIoMiMDAqA0DswxjiomIBSE5I4sXzF+gb6Odqx6xxXZ5ERRP9OJb0tHQ8HD2x6Ko+whD7NI57dx4g5lIA6zSohUG50lzxvaZxr2ETMx5FPeHJo2jS0tJxOe1Op+4d1GQ6d7fg5BFnAFydPGndXuljjdrVuOR3FYCk58m8fPGKBubKBkCfAT3ZumE3oDyZ+lXyK424i4+KJeFJPIq0dAKc/GmaI+7CAm6r4u5uUKQq7hRp6aR/UL68tHW0EWR5n1xZ2bwGzx7Fk/gkAUWaghtOl2hg1VxN5m5AKGmZdqKC7lLKUGlHRERbVxstbS20dLSRa8l59eyvn2bazLwBJfU1e3u/lLqN6xAdFU1sZn7wdPSmXdftSe3nAAAgAElEQVQ2ajJxT+N5kEt+qFyzMnItOYEXrgPw7u17UnPJ+wB65jVJjYrjw+N4xLR0kp0uUNIq/4drvb54k4zX+TvBtI55baKjYlQ+eTn60NaqbS4+PfzkQjYL62+44n2NqnWqqPR9rBN62qo3UHpmrxNOuNAxs07oaduVo0cd+fDhA1FRT7h/P4oWzRsDcMH/CknJKRp2w8PvUaqUPu/evScmJp60tDSOHXPKtR46cOA4ACdPnsXSUunjx3ooNfW9mrwgCAiCQLFiegDo6xcnJT5JTaaaeQ0SHsXx7EkCirR0rjhdxDxHHg8PCFWVpQdBdymdmce/hArm1UmJiufl42dkpCmIPHOZalZN1WTSsqW3lp4u5HIqfS27NkSeCVC71qRpQx4+eMyjqKekpaVx+uRZull3UpPp1qMTRw+dBsDptBvtLFrn+9mrVqtM2bIGXL4USJOmDYl68CibLRe657DVvUdHjhw6pbLVPh+2rgeGEB+fdTJwYdlp3LQBUQ8e8/iR0o7jiXN07dFRLUy3Hh05+qcy7pwd3WlvoRzBtejYlju3Iwm7rRwVT05+QUZm+eo/8Fs2rtsBKOvwpKQUmjZryMMHj3gU9YS0tDROnnChu426Tz2sO3P4kLLX3/G0K990yPKph01noqKeEJ6tgZ4bX+Od/u7de3x9lY3TtLQ0goJvY2JipGnr2JncbanKrYtGuX2fqlmHfmwUaGlpoaOjTdWqlQo87kqUKE6bNs3Zv/eYyq+XL9TftRJfD6lh8BURRfGMKIor/mp4E2Mjnj6JVf2Ojo7D2MQoh4whT58qZRQKBS9evqRMmdJ/1SQABoZlSIx9rvqdFJtImU+8cDv160KQz3WN6zUa1URLR4v4R3G5hitnWJb4mKwGSnzsM8oZlcvXMwqCwIT5P7Fx8e+53jc0Kk9sdLzqd1xMPBVy6K5gWI64TBmFQsHrl68pbVCK8NuRdO7eAblcjmklY+o3qouRSQVK6BcHYMKMMZz2PMjGP1aiX7akms7ShgYacWfwibiz7NeZEJ+soXMDozKscF3Hpss7cNp6KtfRAoBSFQxIiUlU/U6JTaRkhbzTvZWDJWE+ypGVqBt3iQwIZfG1bSy5uo07fiHE34/OM2xhUdawLAkxWR8Gz2KfUc6w7CdCZFGxmimvX75hyY4F7HTbypg5o5DJcq/edAzL8CEmK40+xCaiXUEzjUr1aE0dtw1U2TodbaP8PUdOyhmV5VlsVh5/FveMckZf/vHasWcHvE57aeh7Gh2LsbGhmqyxiSFPnip7uxUKBS9eKOsEY+Os66qwJuphc8PY2JDUbB8I0dGxGBtX0JB5ms3my5evPlkPpaenM378bAID3Xn4MJC6dWvid8RLTaZUBQOSsqVTcmwipSsY5KmzvUNHbvkEqX5r6+ow78xKZp9aRuMcDYrsFDMszeuYrEbJ69gkihtqPnuDIZ353n8tbWf1x3fePo37NW1bEumo3jAwNK5ATHRWHR4THYehkXrcGRmVJzo6qw5/9fIVBgalAKhU2ZTzF05yymU/LVurN1YAvu1jjeOpc0o9xhWIjs6qa2Oi4zHKYcvQqIKarZcvX2FgUFply+vCKRxd9tMqF1uq5y0kO0odWXZiY+IwNCqvIROTKZNlpxTVa1RGROTPE9tx9z3O2PHDAeX0FIDps3/G3fc42/eso2y5MhgZGaqeV+lTnIZPRsYViH6azdaL1xiUKY2eXlF+mTiKVcs3afggiiInTu/Gy+8UQ4b1++rv9JIl9bG27oy3t79GeY+OjsUkZ13xheX2I85OB3j6JIhXr99w997DAo+7ylUq8vx5Epu3rsTH35ENm5eip1c0X3FQqIgZX//vb0BqGACCIJwWBOG6IAihgiCMyrz2WhCEtYIg3BAEwVMQhHKZ130EQVgvCMIlQRBuC4KQZ1ejIAhDBUHYnPl/VUEQAgRBuCYIwuJPhBklCEKgIAiBoqjZWhdz9FQJgmavck6ZgiAvne2/taBagxqc2XZK7Xqp8qX5ed1EtkzZmGfY/+XZ+wz9lotel9UaFjmUf1Z3XvaPHzpDXEw8p87vZ/aSydy4FkJ6ugItLS2MTAy5cTUE+04DCbp2k4Gzh6rrJP8+tf3WgqoNquO87bTqWlJsIjO6TWTiN2P4prelRsPj0/7lLtrMvh2VGlbHa/sZAMpWroBhDRPmtRrD3FajqdWmPtVb1M09cCGSi0v5zg9yLTkNW9Tnt8Xb+LHHWIwrGdHdIY+pPrkNxOSw8+L8NULb/EB411945R9C5V9/yddz5MfYlxZPg/IGVKtTlau+gXnoy0++/uvlLT/hvlS3lpYWo0YNplWrHlSt2oxbt+5gPVZ9ysyX6Gxl354qDavjut1RdW1qm9Es6jmd7ePX8928YZSrlPuak7ziKye39p5nX7vJXFp+mObj1afCVDCvTtq7DyRFPFW7nlue1lCeh/34uASamHWkc/tezJ+9gt93rqF4iWJqcva9e3DquMsn/MhfOsXHJdDYzJKO7b9l7uwVbN25VsPW53QUip18PotcrkWLVk346Ydp2HUbRHebzrT7phVacjkmpkZcuxKElUUfrl8LZv6Sqfmqe/KyNWP2eH7fvJs3b95q3O/epT+W7e1x6DWCET8MpG7dmn/ZzueQy+Xs3/8bv/22i4cPH+cznTT15MeWje0gKldphq6ODvVyTDXK3c6XxZ2WlpxG5mbs3nmIDu3sePvmHRMm/fjZ55IoGKSGgZLhoig2BZoB4wVBKAMUA26IotgE8AXmZ5MvJopiG2AssCufNjYAv4ui2BzIvQsdEEVxuyiKzURRbBYTm4RpxazeBBMTQ2Jj1IM+jY7F1FQpI5fLKamvT1KS5pSALyEpLpEy2XpIDYzKkJRjmB+gQdtG9BrXl5Ujl6qmwAAULV6Umbvn8ueaA9wNiszTTkLsMyoYZ/UAVTAqx/O453nKZ6dhUzMchvXC8coRfpk3lh59ujJuVlbFERcTj5FJ1oeAoXEFEnLojotNwDBTRi6XU1y/OCnJL1AoFCyb+ys9LQcw5vvJ6OuX4NGDxyQnpfD2zTvcXbwBOHfmPFXrV1PTmVvcJecSd/XbNsR+XB/WjlyuFncfSUlI5mnkY+q0qKdxDyAlLpFSxlk9z6WMyvAyl9GFWm0bYDWuF9tHrlLZadi1BVFBd/nwNpUPb1O54xNMlcaaL6zC5lnsc8obZ43qlDMqx/P4xE+EyB72GXdv3yP2cSwKRQYX3C5Sq0HuPn2ITUTHOCuNdIzKkJagnkaKlFeImfGVeMgdvQbVv9Qd1XOVy9bLWc6wHM/j8ufTRyxtLbjgehFFukJDn6mJEbGx8Wry0U9jqWiqXIQpl8spWVKfpKRkoqOzrqvCxqiHzY3o6Fh0dXVVv01MjIiNTdCQMc1mU1+/xCfroUaNlPn6wQPl+pETJ5yp0VT9AyM5LhGDbOlU2qhMriNo9do2wGZcbzaOXKFWlj7KPnuSQPjlUCqZVc31WV7HJlHcOGskoriRAW/icx+pA4h0vEy1ruo93TXtWnE3x2gBQGx0vFqPsLGJocY0ztiYeExMsurwEvolSE5O4cOHNJIzp3fdDA4l6uETqtfI8qFe/dpoaWlxMzgUUPbUmmQbATI2qZCLrTg1W/p52nqsZis7hWVHqSPLjpGxIfGxmnY+jnpl2XlBbEwcARevkZSUwrt37/Hy8KNBo3okJaXw9s1bzjqdB5TTnBo0rEdMtudV+qSZTjHRcZiYZrNVsjjJSSk0bdaIBYunEXzbm9FjhzJx8mhGjhoEoNLx/HkSLk4elC1n8NXe6b9vWcm9ew/ZtOkPAI3ybmJiREzOuiI67ovKbXZSU1NxdvGgVu1qBR53MdFxxETHcT0wBABHR1campvl67kKlQzx6//9DUgNAyXjBUEIAS4DFYGaQAZwJPP+ASD75Pc/AURR9AP0BUEolQ8bbT+GA/bn56ECA0OoUaMqVapURFtbGwcHO5ydPdRknJ09GDxYuRCzdy9rfHwu5kf1J7kXchejqkaUr1geLW0t2tq2J9DjqppMFbOqjFo+hpUjlvIyMWt+upa2FlO3z8T3hDeXz176pJ2w4HAqVTXFuKIRWtpadLHrhJ97/p5/7rjF2Dbvi13LfmxYtIWzx93YvGyb6v6toDCqVK2IaSVjtLW1sLa3wtPVV02Hp6svvfrZANDNthOX/ZVrFYoULaJa6NTWoiUKhUK1aNnL3Y+WbZsB0OabFmqLigHuh9zFsKoR5SqWR66tRWvbdlz3UF8DUdmsKiOWj2HtiGVqcWdgWAbtzJ0ziukXo1azusTmMcXncch9ylUxxMC0HHJtOU1s23DLI1BNxtSsCv2XjWTHyFW8Tnypup4c85waLeshk8uQacmp3rIu8fee5jRR6IQHh2Na1QSjioZoaWvRyc6Si+6fzkNZYSMoUaoEJQ2UIyxN2jYmKvJRrrJvQ+6iW9UInYrlEbS1KG3bnhc58rdW+azh9JJdWvD+L8ZPREgEplVNMMz0qaNdBy555M+nj3Sy64ino5eGvo91gpOzu5q8k7N7Vp3Q2xrvzDrBydkdBwc7dHR0qFKlIjVqVOXqtSA+R2BgCEWLFsHIqALa2tr07Wubaz00aFAfAHr16oGPz6d9jImJp06dmpQtq/wg79SpPbE54vhhyD0qVDGirKmyLLW0bUtwjrJUyawq3y/7kY0jV/AqWx7X0y+Glo5yb43ipUtQs2kdYu/mnobxIQ8oVcUQ/YrlkGnLqdWzFQ89bqjJlKyS1clQpZM5KVHZPuYEgZrWLTXWFwAE3bhFteqVqVTZBG1tbex79cDtrPqUKbezXjgMUI5A2Np3xd/vMgBlypRWTYerXMWUatUr8ygqa4F8rz7WqtGCj7aqVq9Cpcqmmbascc1hy/WsF/0GfJsPW1XUbOX0qTDsBN+4TdXqlamYGXd2vbvjds5bPe7OeePwnTLubOys8Pe7AoCP50XqmdWmaNEiyOVyWrVtTmTmYlh3Vx/aZK4na2fRisiI+9y4fotq2Xzq1dsaVxf1HbrOnfWk/wDlLnN29t244Kv0ybrrAMzrW2Je35KtW/awbu1Wdm4/gJ5eUYoXV46G6OkVxbJTO9zcfL7KO33hgqmULKnP5MlZ/ZfK74cqWbb69szdlqrcft5WsWJ6GBoqOybkcjndunYk4OK1Ao+7hITnREfHUqOmstFoYdGaiPB7SBQO/+93JRIEoQPQGWgtiuJbQRB8gNyWv4t5/J/b77z4ouafQqFgwoS5uDgfRCaXsXfPEcLuRDJ/3hSu3wjB2dmD3bsPs2f3BsLC/ElOSmHQ4KwtySIjAtDXL4GOjjY9bbtibT2AO+F3Wb5sNv362aOnV5QH969x6ZgPx9YfVoXLUGTwx7ztzN63AJlchvdRT57efUK/SQO4f/MegeevMnjWMIroFWXylmkAPI95zsqRS2lt05a6LcwoUaoEln2UC8V+m7KRqLCH5EShULBq9no2HlqDXC7jzOGzPIiM4sepw7kTEoGf+0XqNarDqj+WoF+qBO26tOHHKcPpZzkkX3G3cOYqdh3djFwm5/ifjtyLeMAv00dzKzgMLzc/jh10ZM2WxZy/epqU5BdMHDULgDJlS7Pr6GbEDJG42ASmjJ2r0rt60UbWbFnM7CWTSUpM5sD0HWp2MxQZ7Jm3gxn75iOTy/A56kn03Sf0mfQdD27e48b5awycNYQiekUYv0W5Y0pizDPWjlyOcQ1TBs0ZiiiKCIKAy/bTPIl4TG5kKDI4Pm8XY/fNQiaXcfmoD3F3n9JjYl8e33rA7fPXsZs5CB29IgzbotwNJDn6OTt+WE3w2cvUalOfGW5rQBS54xvMbc8budrJD1Pnr+Ba0E1SUl7SyX4QY0cMprft53fsyYlCkcH6OZtYc2glMpmMs0fOERX5iOFThhIREsFFjwDqNKrNkj8WUqJkcdp0ac3wyUMY0nEEGRkZbFm0jfVH1iAIEHHrLk6HXPIwlMHTudupvn8BglxG4hFP3kc+wXDSAN7eusdLj6uUG2ZDyS4tIF1BesprHk3O2q2n5vFl6FY3RV6sCGZX/uDx1M288sv9A1uhyGDD3E2sPrgCmUzGuSOuREU+YtiUIUSERHLJI4DajWqzZOcCipcsTusurRk6aQjDOim3ZjQ0rUA543KEBNzU0LdUTGfP3iOEhUWyYP4UAq8r64Rduw+zd89GwsP8SU5OYcAgZZ0QFhbJ8eNO3ArxJl2hYPwvs1ULMg/s/w2Lb1pTtqwBUQ8CWbhoDbv3HMbOrhsb1i1BS0vOkSPb+PAhjZUrN3HnTiTz5k3i+vVbuLh4sGfPEXbtWk9oqB9JSSl8//04VRxERFykRAllPWRr2xUbm0GEh99l6dL1nD9/jLS0dB4/jsZ59gG1uMtQZHBg3k4m7ZuDTC7D/6gXMXefYj+xH1G37hN8PhCHmYPR1SvC2C2TAUiMfs6mH1ZiVMOUIctGqcrS2d9Pqe1mlB1RkYHv3L30PDANmVxG2BFfkiKjaTm5Nwk3H/LQ4wYNh1pRsZ0ZGekKUl+84fzErE4Ik5Z1eB2bxMvHzzR0KxQKZk5ZzOGTfyCXy/jzwAkiwu8xbdbPhATdxu2cN4f2H2fz9lVcDnIjJfkFPw5X7kjUqm1zps36GUW6AkWGgmkTF5CSnNWR0PPb7gzoMyqHrUUcPbkTmVyusjV91niCg27jds6Lg/uPs2X7aq4GuZOc/IJRw5V1Q+u2zZk+azzp6QoyMhRMmThfZWveoqn07mNDUb2ihIT5cmDfsUKxc2j/CWZNXcqfJ3Ygl8s4fOAUkeH3mDprHCFBobif8+bP/SfYtG0ll264kpKcwujhUwB48eIl237byzmvo4iiiKeHH57uyl1vli74lU3bVrBo+QwSnycz8afZKBQKpk1ZyPHTu5DL5Bzcf5zw8HvMnP0LQUG3cD3rxYF9x9i6Yw2BwedJTk5hZOYuS3lRrnxZ9h/6DVBOnTt+1AlXVy8mTKBA3+kvX71m5sxfCA+/y9UrrgBs+X0Pe/YcZsKEuTg7HUAul7Nn75HMcjuZG9dv4uziwe49h9m9az1hoRdISkph8PdZ26dGRFxCP1u5tbYZSFJSMieO70JXVwe5XIaPzyX+2HGIBw8eF2jcAUyfsphtO9eio6NNVNQTxo2Zwc+/aG5Z+3eS26Yo/wWErzEf/d+EIAh2wEhRFG0FQagDBAPdAG/gO1EUDwuCMAeoIIriz5kNh3BRFEcLgtAO5fSgBnnoHgo0E0VxnCAIZ4CjoigeEARhDLBaFMXin3o2HV3TQkkcO8O8F4AVNFFpeQ/RFyQpaZrbo34NmutV+rxQAVFW0CkUO2sDlxeKHYBOjTT3QP8abJB/sqgVGBMzCiffAfgn3CkUO1oyeaHYGWCY/52h/lcaKwpn68MlLwM/L1RAZHxZv9M/Hi2hcPIdQKoirVDsvP6Qv93MCoLc5vV/DYppF942okmv7haOU/nk1QTbr17oSqx3KnSf/9+PGACuwGhBEG4CESinEwG8AcwEQbgOvAD6ZQuTLAjCJUAfGJ5PO78AhwRB+AU4USBPLiEhISEhISEhUfj8R0cM/t83DETl1j/dc14XBAFRFOcCczVDcUIUxZm5XM+pew+wJ/P/h0D2zZz/8jamEhISEhISEhISEgXN//uGgYSEhISEhISEhMQX8YlDKf/NSA2DPMhr/r8oih1yXhMEYRjKqULZuSiK4k85ZSUkJCQkJCQkJCT+iUgNgwJAFMXdwO6/+zkkJCQkJCQkJCQKgf/oGoP/97sS/ZOpXKZhoSRO9KsvO3Dpf6FUkdxPuSxo3qV/KBQ7ACV0Cueo9sLaHaZa0dxPiP0aeIbs+LxQATCg6ee3xysoAl7dLxQ78a8LZ4evj/vOFwYZhTQ0Ly+ksqQjL7y+t8LaWacwvxm0Cyn+5ELh5PH3hfhesiyf62aJBc6D9wmfFyog7j67/s/alWhs96+/K9GWc9KuRBIS/yYKq1Eg8e+gsBoF/0UKq1Eg8e+gsBoFEhJ/mf/oiIF08rGEhISEhISEhISEhDRiICEhISEhISEhIfEl/Fen4ksNAwkJCQkJCQkJCYkvQZpKJCEhISEhISEhISHxX0UaMZCQkJCQkJCQkJD4EqQRAwkJCQkJCQkJCQmJ/ypSw+BfhEXHtnhdOYPvNWfG/DJc476Ojjabd67C95ozp90PYlrRGAAtLS3W/rYEtwsn8Aw4zdgJI9T0hYf5M22q5iHNOjo6HDr4O+Fh/lzyd6JyZVPVvenTxhEe5k/obT+sulgAoKurS8BFZ64HehAS7MX8eZNV8h0t23H1iive/o5cuOLC9ZueXA32YPzEUbn6sXP3eq4Ge+DmdYyKlUzU7puYGhEVE8RPP2fFweifhuJ/xYULl53ZvutXdHV16dLFgqBgT27e8mHy5DG5+rd332Zu3vLBx/c0lSop/evYsR3+F524etUV/4tOWFi0VoU553qYoGBPAi6fJeDyWcqWNQDAslM7/K+dJeCGK+MmjMzVp227fiXghitnzx+mYiVj1b26ZrVwdv8T3wAnvC86oqurA8CMOb9w/bYX958GqmQ7dGqL7xUn/APP8tMvI3K1s+WPNfgHnsXJ45AqD3zbxxo33+Oqv8fPb1Kvfm0ADhzbirvfCTwvnWb52nka+9a36NCcA357OOS/j4E/9dew2ahlA3a6bsXrkTsW1t+o3StvXJ61h1ay32cX+7x3YWj6189ImLPsV76x7o/9oNF/WcdHzC0as8FrC5t8t2I/prfGfZuRPVl3fjNrXDcw79AiypqUA6BKvaosPbWSXz02scZ1A21s2n3WVkGn2Ud9d8L8mZpHuT148HfuhPlzMUe5nTZtHHfC/Ll9248umeUW4G7kZYJunCfwmjuXA85q6Px9y0pS3z8h/M5FpkwZm6vNA/u3EBZ6gQt+Z1Q2DQxK4eZ2hMTn4axftzjX+PHzdeTli/sF5o+uri6XMuuh4GAv5mWrhzp0aMvVK65cv+6Bi8tBbt70ITTUL0+f9u//jdBQP/z8HHP4dJjnz++wbt0ilXzx4sW4cuWc6u/p02BWrJpL5y7fcD3oPME3vZg4WTPv6ujosHvvRoJveuHlc5JKmfVd06YN8Q9wxj/AmYuXXbCxtVKF+e33ldyPusrla+fUdFl16cCtmz6EhV74aukUFubP1Cl5pNOBLYSF+eN/IUc6Tf2JsDB/bt/yVct348aNIOjGeYKDPPn5Z/WyMXr0ECIiL5GUHEl0TMhXq8PLlSsDUODppKurg7fvKS5eduF2mB8PH18v0LgbP34kwUGeBN04z/59m9HV1QXA0rItVy6fY4vrZtaeWINxFSMAmnVoyk6fHey+8AcOY/tqPEP9lvXZfHYTZx86066Her02YtZwtp/fyg6vbYxZqBk37Tu2xi3gBOevnmbU+KG5+KfN+h3LOX/1NMdd92JSUflM2tparNg4H2ffI5zx/pMWbZqqwhw4vQ23gBOc8T7EGe9DGJQtraH370bMEL/639+B1DD4lyCTyVi8ahZDHMbQuY09PXt1p2btamoy/Qb14kXKSyya2/DH7/uZMX8CANZ2VujoaNO1fW+sO/ZnwJA+VKpsqtLXoJEl/frZU7duTTV9w4d9R3LyC+rUa8f6jTtYvmw2AHXr1sTBwY6G5h2xthnIpo3LkMlkpKam0tnKgabNutC0mRVdrTrQskUTADZvXs73Q8bR6ZtvKV+uDCEhobRt3oNefWyoVbu6mt2B3/clJeUFLcy7sPW3PcxfOFXt/pLls/D08FP9NjSqwA8/DqazRS/at7JBJpPh4NCTX9ct4lv7oTRt0oW+fXtSp04NNT1DhjqQkvKChg06sHnTHyxeMgOAxMRk+vQZQYsW3Rj1w2R2/rFOPV6GT6B1qx60btWD58+TkMlkLF8zlwF9RvFNS1u+7WOt4dOAwX1ISXlB6ybd2LZlH3MWTAFALpfz2/ZVTJu0AIvWtvSyGUJaWjoA7q4+dO/UTy0PLFk1h8EOY7Bs3RO73j008kD/zDzQrlkPdvy+n1kLJgFw6rgLXS360NWiD7+MnsmTx9GE3Y4AYPTwyVh905tObewpU7Y0HWws1GxOXDqeqYNm8r3lcDrZd6RyzcpqNuOjE1g2cRXnT3uSk9kbpvPn70cZ3GE4P1qPJfl5ioZMfrHv0YWtvy75y+E/IpPJGLH4R5YOWcjEzuNo27M9pjUrqsk8DH3IdJtJTOn2C5fPXmLwzKEApL5LZdPE9Uzq8jNLv1/I0Pkj0NPP+9C+gk6z8LC7Kn0NG1nSP49ym5L8grr12rFh4w6WZSu3/RzsaGTeEZts5fYjnbv0pVlzK1q17qGmr1IlE/r3/5bo6Fg6WNrTz8GOOnXUbQ4b2p+UlBTqmbVn46adLF0yC4D371NZuHANM2bknm729t0xM6vNo0dPC8yf1NRUumTWQ82y1UOCILDrj/UMHDSW5s270qRJA/btO4K5eSccHHpq+DR0aD9SUl5gZvYNmzbtZMmSmdl8WsuMGUvV5F+/fkPLlt1Vf48fR+Ps5MbaXxfS+9thNG/alT59bamdox76fogDKSkvMW/Ykd8272Lh4ukAhIVFYtHOjnatbehlP5QNm5YglysPZjt44Di97Iep6ZHJZGzYsISedt/TyLzjV0unRo0s6dfPjro5dQ/rT3LKC+rVa8fGjTtYtlSpu24d5fvC3LwjNraD2LhxKTKZDLN6tRkx/DvatLWhaTMrevToTI0aVQGwsGiDjU0X0tLSadK4E82bWX21OvzZs0RkMlmBp1Nq6gdsegykfRtbFBkZREfHMnLkpAKJO2NjQ376aTitWlvTuEln5HI5Dg49Adi8aTlDhv7M2G7j8Hb05rvx3yGTyfhpyU/M+X4uP3T8EUu7DlSqWUntGZ5FJ7B20lq8T3urXa/XtC5mzeox2m6erGoAACAASURBVGosP3YeQ61GtWjYKuvwNJlMxoIVMxjZfzzd2/bB5tuu1KhVVU1Hn4H2vEx5SecW9uzeepCp88YD4DD4WwBsLPoxtO9YZi6aiCBknec1efQceloOoKflAJKeF86BjhL/zxsGgiBECYJQ9ivqbyYIwsaC0GXepD5RDx/z5FE0aWnpOJ1ypUt3SzWZLt07cOLwGQDOnvGg7TctAeWWWnp6esjlcooU0SXtQxqVq1XMpi+No0cd6WnbVU1fT1sr9u8/BsCJEy50tGyXeb0rR4868uHDB6KinnD/fhQtmjcG4M2bt4CyJ0BLW1u1nZcoiuiXKEGTZg1JSXnJ/btRpKWlceqEC92tO6vZ7W7dicN/ngLgzGlX2ndone1eZx5FPSEi/J5aGC0tLYoULYJcLkdPryglShTnwf1HREU9IS0tjePHnbCxsVILY2NtxcEDJwA4deosHTq0ASAkJJS4WOVpjmFhkejq6qKjo5Nn2jRu2pCHDx7z+NFT0tLSOH3iLF17dFST6dqjI0f/dATA2dGNdhatAOjQsS1htyNUH+nJySmqg55uBIaQEP9MpcO8aQOiHn60k47jyXNYdVe3Y9WjI8cOK+24OLrTLjMPZMeudw8cT2T1NL5+9UYVh9ra2kBWL0XdxnWIjoom9nEs6WnpeDp6065rGzV9cU/jeXDngUbvRuWalZFryQm8cB2Ad2/fk/o+Nc94/BzNzBtQUr/EXw7/kRrmNYmLiiPhSTzpaelcdLpAsy4t1GRCA27x4b3ylNLIoAgMjJS9irEPY4iLigUgOSGJF89foG+gn6etgk4zdX1pHDnqiG2OcmubR7m1te3KkTzK7afYsX0tISGhpKWnk5aWztFjZ7C1VS9LtrZW7D9wHICTJ12wtGwLwNu377h06RrvUzXTvVgxPWbPmsDNm2GkpaUVqD/Z6yHtzHqoTJnSpKamcvfuA5o3N+fevSjatWtJWloax4455erTAZVPZzV8Sk19n2ecVa9ehfLly/AhNY0HD7LqoRPHnbG26aIma23TmT8PKuuh06fOqeqhd+/eo1AoACiiq0v2nREvXbxGcpJ6I7t5c3Pu34/i4cPHyjr9K6bT0aOOuev+mE4nXbBUpZOVxvuieXNz6tSpwZUrQSo/L/hdxs6uGwA/jhqMi4sH9+9FERX1hJiY+K9ahzdr1uirpNObN29p1qwRUQ8fk5GRUWBxB6Al16Jo5juvqF5RYmPjAeW7tkQJZT1ZrEQxkuITqW1ei5ioGOIex5Gelo7PGV9aW7VSe4b4pwk8DI8iI8cWnKIooqOrg5aOFto62mhpy9U6eBo2MeNR1BPVt4nLaXc6de+gpqNzdwtOHnEGwNXJk9btlfVtjdrVuOR3FYCk58m8fPGKBub18kynfxwZ4tf/+xv4f90w+NqIohgoiuL4gtBl+H/snXdYFUf3+D/DBRTsoiLFrjH23gv2CmLFxJKiJmpib9FYE0tiYouJMZbYO1ZAei+i0kEQxS5VpdkLsL8/7uXChYvl/SL6vr/9PA+P3tkz5+zZOTuzs1PWxJikhBT176TEFKqbVCskk5iolMnOzubRw8dUqlwRRzs3nj59SlCMB4ERrmzfspdyZctq6ItPSMLUtLqGPlOz6tyNT1Try8x8iJFRJUxN89LVec2UeXV0dAgOciUpIRIPD18uBoUBMHnyPOzt9nPo6DaMqlTij43bAEhMTMbEVHN6iYmJMQnxSWq7Dx8+onLlShgaGjBj9jf8/utfGvLJSSls+fNfwqO9iY4L4OHDRyQmJhOfkHeOCQlJheyYmhqrZXLtGBlpDlcOHTqQyIhoXr7M+5T9tn9+J/C8Iz8snK4632okJiRrlI2JSWGfEhPyfHr08BGVK1ekbv3aSMDhEztw9TnB9zMKTzXJ01GNpHx2khNTMCkUA3kySp+UMZAfq2EDOHNSc7rIgePbCL/qw5PHT/B2yBuNqVK9CvcS8zon95PuU7X62/Wla9Q15/HDJ6zasYKdLv8wdcm3haYpfQgqVzciNemB+ndaUipG1Y2KlO89ui9h3iGF0uu3aICuvi4pt5O15FJS3GVWUF9CQhJmb3nfmplWJz5e857IvW8lScLJ8TAXzjsxaeJYtYylZV+ePXvO5di419vMp7uoe6kgK5bPx83NhwTVfVGc/uTWQ4kJkbir6qEHD9LQ09OjTevmmJpWx9DQAHNz07y8heqHd/cpl9GjrbG1tcfEtDrx8Xn+JSYkYVqwbjA1Vsuo6zuVnbZtW3AhyJnAi07MmrFE/QCqjYL18vstp2RMzUw05Mzy+ZqdnU3mQ1V7YWaicQ0S4pMxMzUhOuYK3bp1oHLlihgYlGbAgF7q8mjQoC6du7SnRcsmOLscpXWb5u+3Dn9P5aSjo8O/ezbRtVsHvDwDCAoKK5Zrl5iYzMZN27h+7QJ3bofyMPMR7u7KenvylPnYndnHgYv76T28N0e32GJUvQr389XjD5IeUOU1dV5+LofGEhEYyeHggxwOOUiITyh3r91VH1fWX3nPEsmJKRibVNXQYVy9KskJec8mj1V1XOylq/QZ2AOFQoF5TVOatmiEiVnedf918wrsvA7x/ZzC03Nl3h8fvpXWghDitBAiRAgRLYT4VpX2WAixXggRKoTwEEJUVaV7CyE2CSHOCSEuCSHav0avkRDCVQgRJoTYBoh8x+ao8l8SQsxSpdUWQsQKIXaq0g8KIfoIIQKEEHG5toQQ7VX2w1T/NlSl9xBCOKj+v0IIsUt1vjeEEFo7DEKIb4UQwUKI4MfP0/IdKCxb8OMaogiZlq2bkpOdQ/smfejaeiDffP8lVapVfgt9hRVKUlHpyrw5OTm0bdePWnXa0q5tK5o0Uc5jnznzG6yGjGfe7OXcuHaLVWt+fDe7SPzw4wz+2bJH/TYwlwoVyzNwUG/aNOtF00+6YmhoSNeuhcOg0MdIXuMHKKcqrFy1kOnT8851woSZtG8/gL59RtGlcztGfWZd5Pm+0ScJdBUKOnRszfffzMd6wFgGWvaha/eOhWTf5nyLtpMn06pNM54/e8aVy5ojLuNGTqZNo57ol9KndZe8t8hFxdTboNBV0Lx9U7as3MbkQd9hWtOEgTb935zxA1CUT92GWVC3WX3stp3SSK9YrRLTN87m73mbX389irvM/mN9r7dj0WMo7TsMwNJqHFOnfkXXrh0wMCjNooUzOH7c4S1sFhJ57XVp3rwx9erVIjgk4r34k1sP1S5QD40b9x3r1q1g5cofyMrKIisr6x3tvl3sjxo1hGPH7N7qugjtlTsAwcERdGg3gB7dhzJ33lT1+iNtvM35lnw5SUXajI29xu/r/sbJ8TAO9geIjIpRl4euroIyZQw5e9aNxYvXsH//Fu3nWgx1+Jgxw99bOeXk5LB08a8ct7WnTZvmNGncULvud7x2FStWwMqyH5807ESt2m0oU8aAMZ8PB2DmjG8YYv0F49qPx/WYK98u+6YIPYXTtGFa24Qa9Wswtv14xrQbR4vOLWjaoWn+k9d6jm/j3/FDdiQnpnDKfT+LV80lNCiCrCxlp2rulCVYWozmc8tJtO3YiqE2g9/uhEuSnBL4+wB8lB0DYIIkSW2AtsAMIYQRUAYIlSSpNeADLM8nX0aSpM7Ad8Cu1+hdDvhLktQKsANqAggh2gBfAx2AjsA3Qojcp6P6wB9Ac+BTYAzQFZgH5NY2sUB3ld5lwJoi7H8K9AfaA8uFEHoFBSRJ2i5JUltJktqWLZ338J6cmKLRkzYxNSYl+b5G3qTEFPVbL4VCQbnyZclIz8R65CC8PQPIysoi9UEaIRfCKF+hvIY+czMT9VBkLgnxSdRQvcFRKBRUqFCetLR0EhLy0tV5EzXzZmY+xMf3HP379aBKlco0b9aYi0FhJCYm8/z5C9p1UF5eU9Pq6iHfXBITkzEzN1HbLV++HOlpGbRu24LlP88nNMqTyVO/ZNa8KUz8dhwWPTpz+3Y8qanpZGVl4WDviolpdczN8s7RzMyksJ2EZLVMrp001fC8qVl1Dh/ZxjeT5nDz5h2NawzK+cTHjtnRqnUzEhNT1G8qc8tGm0+5b4mUZVOO9PQMEhNTCAwIIi0tg2fPnuPh5kvzFtqHUpMSUzDJZ6e6qTHJWmIgV0bpkzIGchkyfCCnT2guWMzlxYuXuDppThW6n/SAaqZ5b3+qmlTlQUqq1vwFuZ90n7hL10i6k0R2dg5+LgF80qzBmzO+Z9KSUzEyyRv1qGxiRFpKWiG5Zl1aMHzaKNZOWk3Wy7wHSIOyBizavZTD6w4QF3b1tbaKu8wK6jMzMyHxLe/b+IQk9RvZ3Ly58Zx779+/n8rpM060a9eSevVqU7t2TVatWsjnnw3F3MyE8+ed+LRh/cI2E5LVugveS9ro2KENrVo1Z8P6n7Cy6k+DBnVwd7MtNn9yya2H+vXrAcD5CyH07DWciRNnk52dzbVrt/LyFrhnE/LpfxufcmnWrBG6ugrCwqKUdYx53tthUzMTkpIL1w3mBeq7gnauXrnOkydPaax6sNRGwXpZ67UshnJyc7XFzKw6SYmaI2XK8sjzo0L58qSlZZAQn6RxDczMq5OYpMy7Z88ROnQcSO8+I0lPy+DatZsqXck4O3libmZKSHAEOTk5NPik7nupw9u0bfFeyykxIZlq1arg73eBfv17FMu1692rK7du3eXBgzSysrI4fdqJjp3aUKVKZZo1b0SQaqTex96Xxm0a8yDpAVXz1eNVTKqQ+pb1eOf+nYkNi+X50+c8f/qcYK9gGrX6VH284LNJdVNj7iU/0NCRnHSP6mZ5zyZlVXVcdnY2a5ZuYEjPMUz9Yi7ly5fj9g1lWeU+3zx58hT7k840b93krc5X5v/Ox9oxmCGEiADOAzWABij7TkdVxw+gfDjP5TCAJEm+QHkhhOY4fB7dVXmRJOkskLuapStwSpKkJ5IkPQZOAt1Ux25KkhQlSVIOEA14SMrucBRQWyVTAbAVQlwCNgJFRfBZSZJeSJL0ALgHvPUWLRFh0dSpW4saNc3Q09PFatgA3Jy8NWTcnb0Z8ZlyAdKgIX0556ecu5cQn0Rn1Zw+A0MDWrVtjqebbz59etjYWGPv4Kqhz97BlfHjlbsXjBgxGC/vAHW6jY01+vr61K5dg/r163AxKIwqVSpToYJyvnXp0qXp3asbV65cJz09kwoVytOgQV3CQqL45NP63L2biJ6eHsNGDMbZUXPRqrOjJ599rlyUNGToAPx8AgGwGjCG1s160bpZL7Zt3cumdf/w7/YDxMcn0rZdSwwMSgPQ3aITAf4XqVe/NrVqmaOnp8fIkVacPeumWRiObowdp9yRZtiwQfj4nAOgQoXynDyxm+XLfuP8+bwpJAqFQj1Mraury4CBvYi9HEd4aBR169WiZi3ltRw6YhCuTpoLuFydvLD53BoAS+v+BPieB8Dbw59GTRqq54p26tKOq1eua4+B0EvUqVtTHQPWwwfi5qxpx83Ji1GfKe0Mtu5HgN8F9TEhBJbW/bA7mdcxMCxjQDXjKmr/evXtzp1reY1obHgs5nXMMKlRHV09XXpb9yTA9ZzW8ytIbPgVylUsR4XKFQBo3aUVt67efqu875NrEXGY1DGhWo1q6Orp0sWqG8FuFzVkajepw7e/TGXtxNU8TM17SNfV02X+9kX4nPDivOObr0Nxl5mmPj1G21jjUOC+dSjivnVwcGW0lvvW0NCAsmWVC6gNDQ3o28eC6OgrXLoUi5l5C+rV70By8j2SU+7RrZsVAwf2xsHBrYBNN8aPGwnA8OGD8VbZLIrtO/ZTp25b6tXvwP37D7h1K56Bg8YUiz9F1UOAegeayMjLNGr0Cfb2Lujp6TFqlJVWn8apfRqEt/fbxb2NjTXHjinXeoWERFK3Xl49NGKkJY5n3TXkHc968PlYZT00dNhAfFT1Xa1a5urFxjVqmNLgk7rcvhNfpN3g4Ajq169N7do1lHX6qCHvpZwGDR6DjY21dt255ZRPt4ODW6H2IigoHMgrjxo1TBk6dCBHjyrX2tjZOWNcvSr16tfGwqIT+vp6DBrY573U4TExV99LORlVqUyFCuUICYmkfv069B/Qk+vXbxbLtbtzN5EOHVqp27yePbsSG3tN2daWL0+DBsrFv627teLutTtcibiKWW1TjGsYo6unS48hFpx3O//ass/lfuJ9mndoho5CB4WugmYdm3En31SiqLAYatepgXlNU/T0dBk8tB8ezj4aOjycfRg+2hKAAVa9Oe8fBEBpg9IYGCp96GLRQdlZv3oThUKhnk6pq6tLz35dibusvV38kPyv7kr00X3gTAjRA+gDdJIk6akQwhsorUVUKuL/2n6/6ZiWgTY1+Vdj5eT7nUPe9VsJeEmSNEwIURvwfgtd2bzD9c/OzmbZD2vYZ7sVhULBsUOnibtynTkLvyMyPAZ3Z2+OHjjFxq1r8AlyICMjk2mTFgCw798jrPtzJW4BJxFCYHvoDDFRV9T6JAF79h4lJuYqK5bPIzgkAgcHN3btPsLePZuJjfEnPT2DMeOU29/FxFzl+HF7oiK8yMrOZsbMxeTk5GBiYsyufzehUOigo6PD8eP2nHVUVq6Tp87n2NHtCElwL/keDRrU5VywE4f2H+dK7DUWLp5BeOglnJ08ObjPlr+3/87FcDcy0jP55uvZr702ocGR2J9xwdPvNFlZWURFXmbnzoNcv36TM3b7UCgU7Nt3jMuX41iydDahoVE4nnVn755j7Px3A5FR3qSnZ/DlF8r5ppOnfEHderVYuGgGCxcpZ3wNsRrPkydPOWO3Dz1dXXQUCry9Ajiw15acnBx+nL+Kwyd2olDocPjASa7EXmPBj9MJD7uEq5MXh/Yf569tawkMdSYjPZPJE5RbKGZmPmTblj04e9oiSRIebr64uyor1aU/zWPYyMEYGBoQGu3FkQMnWbpgDQePb0NHoeDowVNcjb3OvEXfExEWjZuzN0cOnOSPf37BP9iRjPRMvpuUt6NTx85tSUpM4c7tvIcLQ0NDdh38i1Kl9NFR6HDO9wJn9tvni7scNi35k3WH1qKjo4PjUSduXb3NhHlfcSXiCgFugXzaoiGr/v2JchXK0rlvJybM/ZIve00kJyeHv3/exqaj6xACrkTFYX/o7NuGfCHmL/+VoLBIMjIe0nvoOL6bOJ4RVu8+NSknO4d/l21n8b4V6Ch08DrmQXzcXUbPGcP1yGsEu19k/I9fU9rQgLl/K++hB4kPWDtpNZ0su9CofRPKVSxHz5HKRcRb5m3mVsxNrbays7OLtczy68t/3y5fPo+QfPftnj2buay6b8fmu29tj9sTWeC+NTauynHbfwHl9K8jR07j6uqt4cOsWUs5fvxffLzPsGv3YS5fvsqyZXMJDYnE4awbu/ccYfeuTcRE+5GWlsH4L/K2ZLxy5Rzly5VDX18PK6v+DLYcS6xqzUJ2djY//7yev/76lahI72LxJ389JFT1kKOqHpo7ZyqDBvdBoaPDwYMnWLJkNsuXz2Pv3qMqn+YQEhLF2bNu7NlzlF27NhEd7UtaWgZffDEtn08BlMvnk6XlOLVPI0daYm39pdq/+XNXcOrMXhQKHfbvsyX2chyLl8wiNDQKJ0cP9u09yvadGwiP9CQ9PZOvv1TWOZ06t2X2nCm8ysoiJyeHObOWkZaqfJe1a88fdO3WASOjSly+GsCaVX+wc/dBZs1aioP9ARQKBXvUPhVvOUVGerF3z1FiLl9l+bJ5hIQqy2n37iPs2f0HMTH+pKdlMG68qpwuK9uLiAhPsrOymTlziXqDhaNHtmNkVIlXr7KYMXMxGRnKTviePUf5d8cGFDo6nDy1h/T0DE6cdHgvdfjuXYcREsVeTk2afso/239HoVAgdAS169Rk7dplxXLtgoLCOHnSkYsXnMnKyiI8PJqdOw+SnZ3N1KkLOHpkB4Y6+jzKfMyGeRvJyc5hy9KtrDmwCh2FAtejrty+eocv5o7nauRVzrtd4JMWn7Bsx1LKVShLxz4d+GLOOL7tMwW/s/606NyCbW5bkSQI9gnmgnvey4vs7Gx+WvQbu479hUJHwfHDZ7h25QYzf5hCVHgMni6+2B48w7q/V+J+8TQZ6ZnM/lY52cKoSiV2HfsLKUciOeke875bCoB+KT12HfsLXV1dFAodzvle5Oj+U/y8Lm9KmMz7Q7ztnMmSQghhDUySJMlKCPEpEA4MALyAzyVJOiKEWAIYS5I0XdVxiJUkaYoQoiuwVZKkZkXo3gzckyRplRBiIOAIVEU5pWgPymlEArgAjEc5ouAgSVJTVf49qt/HVR0AB0mSmgohTgEHJEk6IYRYAXwlSVJtVSdnniRJlqr0x5IkrVPpugRYSpJ0q6hrUcuoeYkUTsKjtxtSLA4qli56a8fi5FnWyzcLFQPl9A1KxA6Aro6iROzUNfjPvzXwrnhE7CgRO2PavL5zWVwEPiq5t1opj0tm+76SWjCe+7BYEihK6F7SV5Tcu7cX2a9KxE5JPTPoleC1U4iSifHnJdQuAfSspvUxqNi58fzem4WKibj7Ia97iVviZHze873fDBUPe5W4zx/diAHgDEwRQkQCV1BOJwJ4AjQRQoQAmcDofHnShRDngPJA4S9/5fETcFgIEYpyncIdAEmSQlUP/bnzCXZKkhSmevh/G34D9goh5gCeb5lHRkZGRkZGRkZG5qPho+sYSJL0AhhYMF0IgSRJS4GlWrKdkCRp0VvoTgXybyA8O9+xDcCGAvK3gKb5fn+l7ZgkSYHAJ/myLlWle6OaViRJ0ooCupsiIyMjIyMjIyPz38cH2jXoffOxLj6WkZGRkZGRkZGRkSlBProRg6KQJKlsEek9CqYJIb4GZhZIDpAk6fuCsjIyMjIyMjIyMjLvwofaNeh981/TMXgXJEnaDez+0OchIyMjIyMjIyMj89/C/2THQEZGRkZGRkZGRua98T+6xkDuGHzEZLx4UiJ2apavViJ2ANqUqVkidkKe3HmzUDHQwtC8ROwAVNIpVSJ2pueUzLaHUHLbiB4K2Vgidto0HVsidgCSKZntSktqG1HTckYlYgegc9m6JWLHNimoROxAyW2dXFpXv0TspD9/XCJ2AKqVqVAidpKfvvnL2cVF+EPt31YpboT4qHYQlSkG5I6BjIyMjIyMjIyMzDsgrzGQkZGRkZGRkZGRkfmfnUokb1cqIyMjIyMjIyMjIyOPGMjIyMjIyMjIyMi8C5I8YiAjIyMjIyMjIyMj87+KPGIgIyMjIyMjIyMj8y7IIwYyH4LefboTHOpGWIQns+dMLnRcX1+f3Xs3ExbhiYfXCWrWNAOgdZvm+J2zx++cPf6BDlha9VPniYz24dwFR/zO2ePtexqA7r06437+FJ4XzzBlxtda7OixeeeveF48w0mXfZjVMAFAV1eX3//6GSffY7ieO8HUmRMAqFO/Fg5eR9R/ETf9+HrymEJ6W1q04g/Pv/nT5x+GTh1R6LjlpCFsdP+Ldc5/sOzQz1QxqwpA7cZ1WH1qLRvc/mSd8x90tuxaKG9J+GQ5cUghva0sWvOX11b+9t3G8O9GFjo+ZJI1mz22sNFlMz8dXkVVlU8AS/et4EDUYRbvXlYoX0GaWrRkjccf/OL9J4OmDi10vN9ES1a5beQnp/XMO7gcI7Mq6mM7rx9lhePvrHD8nek7fnitnXIWrWjk9TeNff/B+LvCZVR5ZC+ahu2jodNGGjptxOizvupj9fYtp1nUQeruXvJGf+D9xsO7sGTNBroP/oyh46b8n/QAdOnZETv/IzgE2jJh2vhCx9t0bMlR1z2ExvvR17KnOr1hkwbsd9jOSZ+DHPfcT3/r3oXy9u/Xg+hLvsTG+LNgfuEPu+vr63Po4FZiY/w5529PrVp52+v+sGAasTH+RF/ypV9fCwBKlSpFYIADIcFuXI87T0pSFJdj/JlfhO6DB7dyOcafgAK6FyyYxuUYfy5d8qWvSjdA3NXzhIW6ExzkyvlAR3X6ihXzcfY9jqP3MRw8j+AbfBafIAf1vadpV4+/dv6GT5ADp10PYl7DFIChIwfh6H1M/XfzfjiNmzYEYMjwgbj4ncDZ9zh7j22lXKVyGjpbWLRivecWNvpsZcjU4YVsDpo0hN/d/2St8yYW54u7KmZVWe2wnl8cN/K722b6jO2voa+4ysXc3BR3V1uiIr2JCPdk+rSJavlDB7cSHOSK7zk7IqK98T1nByjbjouhroREeDCriLbj371/EBLhgZvXcWqo2o5czM1NuJscwbQZEwvl7dm7K35BZzkX6sy0WZO06Nbjn13rORfqzFn3I5jXNFUfa9TkE+xdD+EdaIdnwGlKlVJuf3rCYQ9+QWdx8zuJm99JqlZVbl/bt68FkZFeREf7Mm/ed1r92L9/C9HRvvj6nlFfy8qVK+LicoQHDy6zcePPGnlsbIYQHOxKUJALdnb7qFS5It17dcbjwhm8guyZUkTc/bnzN7yC7DnlegAzVdzp6uqybstKnPyO4xZ4iqmzlHlNTI05dHonboGncAk4yVffjlH7ExHhyaVLPsybN7UIf/7i0iUffH1PU7Om0p9evboSEOBAUJALAQEOWFh0VudZsWI+cXGB3L8fU6icAoKdOB/mwvTZ32j1afvuDZwPc8HJ46g6BmrUNONWcjgefqfw8DvFbxtXAFCmbBl1moffKWJuBPLzL4sK2fQPciTwNbGxbdcGAkOdcXQ/Qo0CseHgehifQHu8As6oY0OmZPn/fsRACDEL2C5J0tMPfS4F0dHRYf2GFQwd8iUJCcl4+Z7C0dGDK7HX1DJffDmKjIxMWrXoxYiRlvy08ge+/nIGl2Ou0qPbULKzszE2rkrA+bM4OXqQnZ0NgOWgsaSlKvdBr2pYkZ/WLuSLkVNJTkzhtNtB3J19uHb1htqOzdihPMx4RK/21lgO688Py2cyY9JCBln3Qb+UPgO721DaoDSuASewl3ANWAAAIABJREFUO+nEzWu3sez5mdqPwCgXXM56YYKehn8TV05m5djlpCWn8ovdOoLdLxIfd1ctczP6Jj9YzuHl85f0GzeA8Yu+YuO033nx7AV/zt5E8q0kKlWrzNqz6wn3DePpwydq3SXh0wXnwEJl9u2qKawYu5TUpFR+s9/ARbcLGj7diL7BvMFzePn8Bf3HDeSLH79m/fe/AXB620lKGZSi/9iBr40NoaPDuJ8nsX7cz6Qlp7HM7lfC3YJJvBavlrkTc5OfrX7g5fOX9BjXj1GLxvPPNOV+/i+fv2TFoPmvtaFyiBqrJnNt7HJeJaXS0H4dmW4XeZ7PH4AMe3/il20vlD1l2yl0DEpRRfXA9HpT7y8e3pWhg/oyZsQQfly57j/Kn9+nH3+Zy7c2M0lJusdh5114u/px4+ottUxSQjJLZq7kq+80v4Hw/NlzFk//mTs346lqXIUjrrs553WBRw8fq3Vv/mM1AwZ9Tnx8EucDHbF3cOXy5Ti1jglff056eiafNu6Kjc0QflmzmDFjp9KoUQNsbKxp3rIXpqbGuDgdoVGTbrx48YI+/Wx49uw5sTH+xMcnMnPmUjZvXo2DFt0Z6Zk0Uules2YxY1W6R9tY00Kl29npCI2bdFN/D6FP31Gkpmp+g2H9+q1sX78LHR0dQmK98PU8x7zpS7FzP4y7szdxV/Lu29HjhpOZ8RCLdpZYDRvAwuWzmDZpAaePO3L6uLKz0bBRA3Ye+IOYS1dQKBQsX/MDfToPJT0tg0XLZ9Pvy8Gc2HQEUN5LX6+czJqxy0lNTmW13e+EuF8kIS7vXroVfYPFlnN5+fwlfcYNYMyiL9k8bR3p99JZPvwHsl5mUcqwNL+7bibUI0itb3uYS7GUS1ZWFvMX/ERY+CXKli3DxQvOuHv4cvlyHGPGKh8uy+kbsHLNIh4+fISOjg6/b1jBsCFfkpiQjKfvSZwKtB3jvxxFZkYmbVr0ZvjIwaxYuYCJX85UH1+9djHubr5aY3rNuiWMHjqJpMQUnLyO4urkxdUr19Uyn48fQWbGQzq3HoD18IEsWTGXKRPmolAo+Gv7WqZPXkjMpStUqlSBV6+y1PmmfbOAiPBoQPkdAx0dHf74YxWDB48lPj6JgAB7HBzciI3Nu5ZffTWajIxMmjTpzqhRVqxatYjx47/n+fMX/PTTeho3bkiTJp+o5RUKBevWraBVq96kpqazevWPfPnN5wwdNZjxIyaTnJjCGfdDuDt7cy1f3NmMG0ZmxkN6trPCUhV30yctYJB1X/T19RnYbSSlDUrjdu4kdiecefnyJauXrSM6MpYyZQ2x9ziCnasHmzatZPDgsSQkJOPvb4eDg3shf9LTM2na1IJRo6xYvXoh48dPIzU1nZEjJ5CUdI/GjT/B3n4/9ep1AMDR0Z1//tlLVJS3Rjn9un4ZNkMnkJiQgouXLS6OnhrlNOaLkWRkPKRjq/4MHTGIpT/N5duv5wBw++YdencbplH2Tx4/0Uhz9TmBo72bhs1f1i3FZuhEkhJTcPY6Vig2xowfSUZGJp1aD8B6+CCWrJjH5AlzUCgUbNn+G9Mm/6CKjYoasfExIq8x+N9lFmD4Pg0IIf6jDlibti24ceM2t27d5dWrV5w87sDgwX00ZAYN7sOhgycBOH3KCYsenQB49uy5uhNQunQpJKno/XZbtG7K7Zt3uXs7gVevsnA45ULfgT00ZPoM7MGJI/YAONm507lbewAkCQwNS6NQKChduhSvXr3i8SPNh7HO3dtz+1Y8ifFJGun1WzYg+VYy9+6mkPUqiwB7P9r2ba8hEx0YxcvnLwG4GnaFyibKt0hJNxNJvqXUl34vjcwHmZSvXL7EfbqfcF8jvUHLBiTdSiLljtInf3tf2vfroCFzKTCKl89fqH0yMsn7sFNUQCTPHj/jTdRtWZ97t5O5f/ce2a+yuGAfQMt+7TRkYgOj1dfuRlgclaq/+wekDFs24MWtZF7eSUF6lUW6vR8V+rV/c0YVjwMiyXkLf+D9xsO70rZlMyqUL/dmwTfQtFVj7tyMJ+FOIlmvsnA+7U7P/t01ZBLvJhN3+XqhD4ndvnGXOzeVD6f3Ux6Q9iCdSkYV1cfbt2vF9eu3uHnzDq9eveLYsTMMsdLsgA2x6sf+/bYAnDhxll49u6rS+3Ps2BlevnzJrVt3uX79Fu3btQLgyZOntG/Xihs3b5OdI/Hq1SuOHjuDVQHdVkXotrLqz9EidBfFo0fKzk7L1k3JzHjIo8dPePUqC/tTzvQd2FNDtu/AHpw4onwr7mjnRpfuHQrpGzJiIHYnnQDlB5iEAEND5QfAypYrQ3pKmlpWGXdJ3LubQvarLALt/WnbV1NnTOAlddxdyxd32a+yyHqpfHjR09dD6AhqN6mr1ldc5ZKcfI+w8EsAPH78hNjYOMxMqxfye9jwQZywtVe3HbfVbcdZBhVoOwYO7sPhg6cAOHPKWd12AAyy7MPtm3eJzdeZyaVVm2bcunGHO7fjefXqFWdOONF/UC8NmQGDenHssHI02uGMK90sOgJg0asLly9dJebSFQDS0zNf+wG9du1aasS4ra09VvlGv0EZhwcOHAfg5ElHevbsAsDTp884dy6IFy+ea8gr40FQpoyy2S9fviz6+voa7YUy7npo5Os7sKc67pzs3OjcPbe9kDA0NMhrL15m8fjRY+6nPCA6MhaAJ4+fci3uBj16dOL69VvqNt3W1h5Ly74adiwt+3Lw4Am1Pz16KP2JiIgmKekeADExVylVqhT6+so36hcvhpGcfE9DT+s2zbl54w63bynL6fRJRwYM1hx1HDCoN8cOKcvJ/rQLXS068bbUqVuLKlUqc/5csDqtlcpmbmycPuFYKDb6D+rFscNnAHA440JXVWz06NWFmEtX8sVGRol9XFFGkw/WMRBCnBZChAghooUQ36rSHgsh1gshQoUQHkKIqqp0byHEJiHEOSHEJSFEkU8mQoiyQojdQogoIUSkEGKEKn2rECJYZe8nVdoMwBTwEkJ4qdL6CSECVedgK4Qoq0ofJISIFUL4CyE2CyEcVOmVVb5ECiHOCyGaq9JXCCG2CyFcgX1CCD8hRMt85xmQK1sUpqbGJOR7mE5ISMbE1FhDxsS0ulomOzubh5mPqGxUCVB2LM4HOXHugiOzZy5VdxSQJE6f2YOP3xm++vozqptUIykxRa0zKTEFY5OqGnaMTaqRlJCstvPo4WMqVa6Ik507T58+53y0G/7hTuzYso/MjIcaea2G9cf+pHMh/ypXNyI16YH6d1pSKkaveXjtPbovYd4hhdLrt2iArr4uKbeT1Wkf0qcHiXk+pSalYmRctE99Rvcl1KuwT2+ionFl0vLZSU9KpZJx5SLlu9n0Iso7TP1br5Q+y+zWsvjUGloV6FDkR7+6ES/z2XmZlIqeFn8qDurEpy5/UPufH9AzqVLo+NvwPuPhQ2FsUpWUxLwGOyXpHtUKxOHb0LRVY/T09Lh7K0GdZmpWnbvxierf8QlJmBZ4WMwvk52dTWbmQ4yMKmFqqiWvmTKvjo4O+/dvwaJ7Jzw8fLkYFEZCQlKhB9GidJuZVic+n+6EfLolScLJ8TAXzjsxaaLmCMn8xdP599CfVDKqyIZftgDK+7a6ieaX2aubGJOourfz37f5sRranzMnlB2DrKwslsxbjYv/CYKiPWjQsB5eR93VspWqV9aIu9SkVCpVL/pe6jG6DxHeoerflU2qsNZ5E3+d34ndPyfRLaWnoa+4yiWXWrXMadmiKRcuhmmkd+7Sjnv3HnDj+m1MCrQdiVrajvzti7LteExlo0oYGhowc/Zk1v7yp1b/q5sYk5CQd28lJSZrL6N8devDh4+oXLki9erXQkLi8IntuPoc57sZmlN2Nm5ZjZvfSWbPn6I6Ry2xVMiPPJlcW0aqNlAbWVlZzJixmOBgV27eDKZRowZcirysbgsAkhPvUd1E046xSTWSEotqL55xIcadgAgXdmzZW6i9MKthSuNmn5Ke/pB4jTY9CbMC5fs2/gwbNoiIiGhevnxZpJ/VTY1JTNCMgYI+mZhUIyEhLwYeqcoJoGYtc9z9TnLq7H46dGpTSP+wkYM5c8qpkL5EjdhIwaSQzbzzym+zbv3aSMDhEztw9TnB91qmsH105JTA3wfgQ44YTJAkqQ3QFpghhDACygChkiS1BnyA5fnky0iS1Bn4Dtj1Gr1LgUxJkppJktQc8FSlL5YkqS3QHLAQQjSXJGkzkAj0lCSppxCiCrAE6KM6h2BgjhCiNLANGChJUlcgf8v+ExCmsvUjsC/fsTaAtSRJY4CdwFcAQohPgFKSJEUWPHkhxLeqDkxwdvbzgocp+OJf29fIc0cHQoIj6NhuID0thjFn7hT1fL1+fWzo3tWaEcMnMOnbcdRvWPct7BQ2JEkSLVo3ISc7m05N+2HRZjCTvhtPjVp5c1X19HTpPcACJzu3Qvm1UdTIRrdhFtRtVh+7bac00itWq8T0jbP5e95mzbxar8v796kondqwGNaDes3rc3rbSa3HX8e72Ok4tBu1m9fDefsZddr8zlP4ecgPbJ+xic+XfU3VmsZa82q7jgUvZKZ7ENGdvyG2/0we+UdQa8NMLZn+M4otHj4U71BORVGlmhFr/lzGslmrNPK+TQxol3l93pycHBYuWsWRo2do17YVTZo0LDbdFj2G0r7DACytxjF16ld07Zr3Zv731X+yeN4qbt+8y5eTPn+NT4XUa8i0bNOMZ8+ec1U1bUZXV5dxE2wY1MOGdk16ExtzlaHf561fEVori8JJAF1VcWefL+7Skh7ww4BZzO4+he4jelKmfJnXnp/Sh3e/dgBlyhhy7OgO5sxbrh5lyWXEKEtO2Dq8Rv+bGw9Jkli4eCZbt+zmyRPts2u16n4bGUlCodClfcfWfP/NAqwHjGOgZR+6dle+Mf7+mwX06jKUoQPH0aFTG8aOHfF/iPGi7zFdXV2+/XY8HTsOok6dtkRFXWaAZa9Ccm9rp0XrpmRnZ9OxSV+6tx7EpO+/0GgvDMsYsHXPelYu/r3Q6MV/4k+jRg1YtWoh06YtKiSnqUdL4lvFAKQk36N1k1706Tac5Yt/ZevOdZQtpxnXQ0cM4tTxs28+d94u9nUVCjp0bM3338zHesBYjdiQKVk+ZMdghhAiAjgP1AAaoOwfHVUdPwDkX0F4GECSJF+gvBBC8xVRHn2ALbk/JEnKncxqI4QIBcKAJkBjLXk7qtIDhBDhwJdALeBT4IYkSTfzn4uKrsB+lS1PwEgIUUF1zE6SpNx5FLaApRBCD5gA7NF28pIkbZckqa0kSW1TUjIxMzdRHzMzq05yUoqGfGJCslpGoVBQvkI50tMyNGSuXrnOk6fPaNxY2cDnDjk+uJ+Kg70rlY0qarxNMjE15l6y5hSZ5MQUTFRvNhQKBeXKlyUjPZMhIwbi43GOrKwsUh+kE3IhnGYt8y6tRZ+uREfG8uB+GgVJS07FKN/b5comRqSlFJZr1qUFw6eNYu2k1ephewCDsgYs2r2Uw+sOEBd2tcD53vsgPqUmPaCKaZ5PRiZGpN0rLNe8awtGTrPhl4mrNHx6W9KTU6mcz04lEyMy7qUXkmvcpRmW00awedKvGnZyZe/fvUfs+WhqNqmj1c7LpFT089nRNzHiVQF/sjMeIal0px5yxbBZvXf2B95vPHwoUhLvYWya9zbV2KQa95MfvCaHJmXKGrLlwHr+XLudyNBojWMJ8UnUMM9buGduZkJSgfohv4xCoaBChfKkpaWTkKAlb74RtoT4JIyrVcHH9xz9+vXAzMyExLfUHZ+QhHk+3Wb5dOee3/37qZw+40S7di01dCYnpvD82XMGWimnvZiYGpNS4L5NSkxRvzXOf9/mYjVsgHoaEUDjZsp6784t5bQsh9OuNGjzqfp4wbgzMjHSmGqUS9MuzRk6bSTrJq3Res+m30sn/updyhtV0NBXXOWiq6uL7dEdHD58itOnNd/UKhQKLIf059QJ5YNa/nYBlCMUyUmaU00Ktx1lSU/LoG27Fvy0cgER0d5M/e4r5sybyjeT8xbNJyUma7zlNjGtTkoB3UmJyeqRDoVCQfny5UhPzyQpMZnAgCDS0jJ49uw5nm6+NGuhrFtzz+/J46ecPH6Wtm1bkKAtlgrYyi+TayutQBuYnxYqezdu3AbgxAkHTM1N1G0BQHXTaqQUmJqTnJiCiWnh9sJ65EB8PXPbizSCL4TTvGUTQFlmW/ds4MxxR1wcPEhISMZco003UY9+vY0/ZmbVOXp0O5MmzeHmzTtF+giQlJCCqVmBGEguWE4pmJnlxUC58uVIT8/g5ctXpKcrbUaGR3Pr5l3q1c9rIxo3bYiuri6R4Zp1UmJiisYIl4mpceG4S0xWn1d+m4mJKRqx4eHmS/MW2h7TPh6knPf/9yH4IB0DIUQPlA/wnSRJaoHyYb20FlGpiP9r+61WX/CYEKIOMA/orXqzf7YIewJwkySppeqvsSRJE9H+3jR/nqLOWz0xXbW42Q2wBmyAQ6/RCUBoSCT16tWmVi1z9PT0GD7SEkdHDw0ZR0cPxoxV7qIxdNhAfH2Ui2Fr1TJHoVAAUKOGKQ0a1OH2nXgMDQ0oW1bZ8zc0NKBXr274eJyjdt2amNc0RU9PF8th/XF39taw4+Hsw4jPrAAYOKQPgX5BACTGJ9O5m3IqioFhaVq2bc6NuFvqfFbDB2idcgNwLSIOkzomVKtRDV09XbpYdSPY7aKGTO0mdfj2l6msnbiah6l5jb+uni7zty/C54QX5x3PFdIdGRb9QXyKi4jDpI4p1WoYo6unS1er7gQV8KlOk7pM/eV71kxcSWY+n96FmxHXMK5tQhXzaij0dOlg1YVwtyANmZpN6vDFmslsnvQrj1LzhrYNy5dBV1+57KVspXI0aPMpSfkWWubnaUQcpeqYoF+jGkJPl0pW3cgs4I9utbxh7gp92/P8mnZdb+J9xsOHIjr8MrXq1sCspgm6eroMGNoHb1e/t8qrq6fLpt1rsbd1ws3es9DxoOBw6tevQ+3aNdDT08PGxhp7B1cNGXsHV8aPHwXAiBGD8fIOUKfb2Fijr69P7do1qF+/DheDwqhSpTIVKpQnKDicBg3qMmhgH65fv8VoG2scCuh2KEK3g4Mro7XoLlj39O1jQXS0cj5xfdVDR0RYNA0a1iMxIQk9PV2shg3Azclbw667szcjPlPuBjZoSF/O+eXFiBCCwdb9NDoGyUn3aPBJXfUUy249Omos0r8eEUf1OiZUraG8lzpZdSVES9xN+uU71k1coxF3lasboacaiS1TvgwN235KuGeoWl9xlQvAju3ruRx7jU1/FF7k36d3N+Ku3iBRNdVF2XbUoqa67RiMU4G2w9nRg8/HKheSWg8bgK/PeeU17fc5LZr0oEWTHmz9ew8b1m1lx7b96nzhoZeoU68WNWqZoaenh/WIgbg4eWnodnHywuZz5U5pltb98Pe9AIC3RwCNmzTEwEC5hqtjl3ZcvXINhUKhnsKiq6tL3/4WREdfJTg4QiPGR42ywsFBc6TWwcGNceOUu78NHz4Ib+/X3/+JiSl8+mkDqlRRThfr3bsb4cFRqvbCTB137k4+Gvnyx93AIX0JVMVdQnwynVTr0wwMDWjVthnX45TvENduXsG1qzf4d6vy+uX6U6tWnj9nz2r6c/asO2PHjlD74+Oj9KdChfKcPLmbZct+IzAwmDcRFhpF3Xq1qKkqp6HDB+HiqFmPuDh6YjNGWU5WQ/vj76uMASOjSujoKB8Pa9U2p269Wty+lbcJxPCRgwuNFgCEF7Q5YhCuBWLD1ckLm8+tAbC07k+Ayqa3hz+N8sVGpy7tNBYty5QcH2pXogpAuiRJT4UQn6J8Uw/KjspI4AgwBvDPl2c0yrUAXVFOFSrqicoVmIZyUTFCiEpAeZQP6ZlCCGNgIOCtkn8ElAMeoBy92CKEqC9J0jUhhCFgDsQCdYUQtSVJuqU6l1x8gbHASlWH54EkSQ+1DZehnE5kD/hJklT4lVQBsrOzmTf3J06e3oNCocOB/ceJvRzHj0tmERYahZOjB/v3HmP7zvWERXiSnp7BhK+U0zg6dmrL7LmTefUqCyknh7mzl5OWmk7t2jU4cHgrALq6Co4fs8fb3Z8VC2Gv7d/o6Ohge+gMcVduMGvhVKLCY/Bw9uHowdNs+HsVnhfPkJnxkBnfLARg/66j/Lb5J5z9jyOE4PjhM8TGKBeslTYoTVeLDiyZs0qrfznZOfy7bDuL961AR6GD1zEP4uPuMnrOGK5HXiPY/SLjf/ya0oYGzP17AQAPEh+wdtJqOll2oVH7JpSrWI6eI5XDwFvmbeZWzE31tVuxcO0H8WnH0n9Yvv8ndBQ6eBx15+7VO3w+ZyzXouIIcrvIl4u/prRhaeZvVdq7n3ifXyYq9a0+/itm9cwpXaY0Oy7sZsv8zYT7hmm1c2DZTubsW4KOQgf/Y54kxsUzdPZobkVdJ9w9GJtF4yllWJrv/p4LQGrCA/78Zi0m9c35cs23SJKEEALHrac0HpQ0gzCH+KXbqbd/BUKhQ+pRD55fvUv1OWN4GnWNh24Xqfq1JRX6toesbLIyHnN77h/q7A2Or6FUPXMUZUrT5MK/3Jn/F4+0+PO+4+Fdmb/8V4LCIsnIeEjvoeP4buJ4Rli9eWelgmRnZ7Pmx/VsPbwJhUKH04cduH7lJt8t+IaY8Mt4u/rTpGUjNu36lfIVy2HRtytT509iuMVY+g/pTeuOLalQqTxDRg8CYOnMVVyJjlPrnjlrCY5nD6HQ0WHP3qPExFxlxfJ5BIdE4ODgxq7dR9i7ZzOxMf6kp2cwZpxyu8eYmKscP25PVIQXWdnZzJi5mJycHExMjNn1r/JchY6gbt2a/LZ2mVr38uXzCMmne8+ezVxW6R6bT7ftcXsiC+g2Nq7Kcdt/AVDoKjhy5DSurt4ArF69iCafNiQnJ4fbN+OpV78OHoFnOHboNHFXrjNn4XdEhsfg7uzN0QOn2Lh1DT5BDmRkZDJt0gL19e7QuQ1JiSncvZ23FuNe8n02/f4Ptg67efUqi4S7SRz9Yaf6eE52DnuW7WDRvuXoKBR4H3MnPu4uI+d8zs3Ia4S4BzHmx68obViamaq4S028z7pJazCrb864JV+r7yWH7We4ffmmWt9M6cdiKZcundsxftxIIqNiCA5SdjKWLv0VJ2flg56NjTUnbO014m7B3J84cXo3CoWCg/ttib0cx6IlMwkPvaRuO/7ZuZ6QCA/S0zOY+NWst47pH+ev5vCJHSgUOhw5cIqrsdeY/+M0IsKicXXy4vD+E/y5bS3nQp3JSM9gyoR5AGRmPmTblr04eR5DkiQ83HzxcPXFwNCAwyd3oKuni0JHgZ9PILt2HSInJ4dZs5Zib78fhULB3r1HuXz5KsuWzSEkJIqzZ93Ys+cou3ZtIjral7S0DL74Ypr6XK9cCaBcuXLo6+thZdUfS8txxMbGsXr1JtzdbXn1Kos7dxJYMvNn/H3Os892KzoKHWxVcTd74XdEhUfj7uyjirvVeAXZk5nxkOmquNv/7xF+//NnXAJOIgQcP6RsL9p2aMXw0VbERl/lrLdyIsSPS39l9uxl2NvvU/lzjMuX41i6dA6hoZGcPeuu8mcjly75kJ6ewfjxSn+mTPmSevVqs3DhdBYunA6AldV47t9PZfXqRYwebY2hoQHXrp1n9+4j/Pn7NhbNW8mRk/+iUOhw+MAJrsReY8GP04kIu4SLkxeH9h/nr+2/cT7MhYz0TCZPUO5I1LFLOxb8OJ3srGyyc7JZMHuFxqjckGEDGTPy2yJiYxWHT+xU2TypthkedgnXXJvb1hIY6qyyOTdfbOzB2dNWHRvurj6FbHxM/K/uSiQ+xDxcIUQp4DRgBlxBOWd/BeAAbAQGAZnAaEmS7gshvIFAwALlQ/4ESZIuFtasXHyMcipRGyAb+EmSpJNCiD1AB+AG8ALlNJ89QojpwPdAkmqdQS9gLVBKpXKJJEl2Qggr4HeUHYiLgLEkSWOFEJWB3UAd4CnwrSRJkUKIFcBjSZI09jsUQsQCsyRJ0v7KOR8VytYrkcIxKv2f797yrrQpU7NE7IQ8ef0wa3HRwtD8zULFRCWdUm8WKgam57wqETsAa143FleMHArZWCJ22jQd+2ahYiImrWRivISKCNNy775r1n9K57KF11W9D2yTgt4sVEyU0zcoETuldUtmb/n054/fLFRMmJQperFycZL8tOgpTsVN+RKKhyJegr4XkjMul5yxt+Beb4v3/oxWzcPntT4LIQYAfwAKYKckSb9qkbFB+YwtARGqda9F8kFGDCRJeoHyrb0GQggkSVqKcgFxQU5IkvT61TZK3Y9Rrg0omP5VEfJ/An/m++0JaNumxUuSpE+F8i7YgnJhMqo3/9Za9K4omCaEMEU5KuJa8JiMjIyMjIyMjMx/Bx96xEAIoUD5PNoXiAeChBB2kiTF5JNpACwCukiSlC6EqKZdWx7ydwzenm9UC5KjUU6F2vYumYUQXwAXUO6O9D86ACUjIyMjIyMjI1MCtAeuSZJ0Q5Kklyin4Rd8Uf0NsCV3Ix5Jku7xBj6qLx9LklS2iPQeBdOEEF8DBfdFDJAkqfD354sBSZI2opzm9J/m34fmVqYyMjIyMjIyMjL/jUjvf2aT6jtf+Rd0bJckKXcHAjPgbr5j8SinzOfnE5WeAJTTjVa8aSr7R9UxeBckSdqNcm6/jIyMjIyMjIyMzP8Uqk5A4a3IlLxuV8xcdFF+DqAHys10/IQQTSVJKnLBy39tx0BGRkZGRkZGRkbmQ/ARTAqPR/kdsFzMUX60t6DMeUmSXgE3hRBXUHYUitwZQV5jICMjIyMjIyMjI/PfRRDQQAhRRwihD3wG2BWQOQ30BBBCVEE5tejG65R+kO1KZd4OXX2zEimc8qUMS8IMANkfQRf7v5UaZaqWiJ0qelq+PlmWAAAgAElEQVSX+rwXrj1NLhE7lfXLlYidkEsHS8QOgIFptxKzVRKU1DaYSlt6JWKnJLdyfPTiWYnZKgnK6mv7Bun7QVdHUSJ2SnILVh1RMu99dUowxp88vfVRbVea1LXne39GM/H3etN2pYOATSjXD+ySJGm1EOJnIFi11b4A1gMDUG7hv1qSpCOv0ylPJZKRkZGRkZGRkZF5Bz6G95ySJDkCjgXSluX7vwTMUf29FfJUIhkZGRkZGRkZGRkZecRARkZGRkZGRkZG5l2QSmC70g+BPGIgIyMjIyMjIyMjIyOPGMjIyMjIyMjIyMi8Cx/DGoP3gTxiICMjIyMjIyMjIyMjdww+dvr360H0JV9iY/xZMP/7Qsf19fU5dHArsTH+nPO3p1Ytc/WxHxZMIzbGn+hLvvTrawFAqVKlCAxwICTYjYhwT5YvmwtA7z7duBDqQnC4OzPnfKvVzr97NhEc7o6b53Fq1DTTOG5mbsKdpHCmzZioTitfoRx79v/J+RBnzgc70659S5Wt7gSHuhEW4cnsOZO12tq9dzNhEZ54eJ2gpspW6zbN8Ttnj985e/wDHbC06qfOU6FCOfYd+IugUFcuhrjQrn2rErNTUj61aNtUQ2eXnh2xDziK43lbJk4fX8hmm44tOea2l/AEf/pa9tQ49s/hjZy76saWA+sK5StI+x7t2Oezm4P+exnz/WeFjjfv0IztTlvxuOWCxeC8LTRbdm7BTpd/1H+u1xzp2r/za2316N0Fnwv2+Ac78v3MiYWO6+vr8fe/6/APdsTe7RDmNUwBGDZyMC4+x9V/dx5E0rhpwyLtdOnZETv/IzgE2jJhmvZrd9R1D6HxfhrXrmGTBux32M5Jn4Mc99xPf+ver/XnTSxZs4Hugz9j6Lgp/1H+4q4fAHZsX09ifATX4s6/N93hYR6F9E2Z8iWh4R7EXPbjTnwYEVFezJlb+Lro6+uzd9+fRER54eVzSn0v9ezVFb8AOy5cdMIvwA4Li07qPCNGDOb8BSeCgl1YuWohAL36dON8iDMXw92YMVtbnafHzt2buBjuhounrdY671ZiGN9Pn5Dnw/df4X/hLH7nHdi+awOlSunTq3c3AoOduRjmyozZ32i1s2P3Ri6GueLscUxtp0ZNM+4kR+Dldxovv9P8vvEnAAwMSnPo2DbOBTnhd96BpSvmqnX17WtBZKQX0dG+zJv3ndZrt3//FqKjffH1PaMus8qVK+LicoQHDy6zcePPGnlsbIYQHOxKUJALdnb7MDKqVCJ2KleuVEjvf1pmNWqacTclEi//M3j5n2Gd6lrmp2fvrvgHORIY6sy0WZO06t62awOBoc44uh+hRk1TlW5TbiaF4e53Ene/k6zdsFydx3rYQDwDTuMTaM/Sn+YB0K9vD6IivYmJ9ivy2h3Y/zcx0X74+doVuHZHSX0Qy6aNKzXyuLoeIyrSm4sXnLl4wZmqVY0AZTxERHhy6ZIP8+ZN1Wpr//6/uHTJB1/f09SsqbTVq1dXAgIcCApyISDAAQuLvHr7zJm9XLjgREiIG5s3r0ZHR4e+fS0IC/cgMsqbuXO129m77y8io7zx9tG04x9gz8WLzvgH2Gvcs7kcs91BUJBLofSPASlHvPe/D4HcMfiI0dHRYfMfq7G0GkezFj0ZPXoojRo10JCZ8PXnpKdn8mnjrmzavINf1iwGoFGjBtjYWNO8ZS8GW47lz81r0NHR4cWLF/TpZ0Obtn35f+ydd1gUx//HX8NxINg7HCDYTWJBBbtixQLYS2KLSTTdGmPUqDHGNBNTvqlGYzf2gqLYK1aQpoAoHQ6wAnbq/P44ODmK9cDE376eZ58Hdj8z75nPznxm92Z2t6WTKz1dO9OqdQsWLJzL0IFjaevcm0GD3WnYsJ6BzsjRg0lNvYmTY3f++G0Zc+d9bHD8q28+5cC+owb7vl4wiwP7j9KmZS86tvUgPDwSExMTFv4wl8ED36SVU08GDfGgYSNDrdGvDyE1NY3mzbry+2/L+PyLTwAIC71I54796djOg0H93+Cn/81HpdK9f/qbBXPYv+8ozi1cad/GnYhLUaWiczE8otTqFHUxxqBtzPpmKu8Nn0zfjq/RZ4ArdRo4GGgmaS8za+IX7Nqyl4Is+30NMz4sPDgWxMTEhInzx/PJqJm83uUtuvbrgn39WgY2V7RX+GbKAvZvO2iwP/BEEGN7vsvYnu8yedjH3L9/H98jZx+qNX/BLEYNfY8ubfvSb1Af6jesY2Dz6siBpKXepINTHxb/sYqZc3VvYNu6aSc9XQbT02UwE9+dQXycltDz4cXqzPz6I94bPoX+nV6j94AeRfgumVkTv8B76z6D/ffv3efT8fMY6DKC916bzLR5kyhf4em/+9C/Tw/+/GH+U6UtifgAsHLlBjz6jkJjXbNE8nZzH1GoLp1d2uHm3p12bdzIys6mf9/XcWrhypAhfWlUoC+9PmYoqalpNGvShd9++Vt/oX/9+g2GDB5L61a9eWfcVBb//QOgu6Ca/9UM3N1G4OzUkxo1quHSpR3fLvyMYYPG0d65DwMHu9OgYV0DnRGjdX22lWMP/vxtOZ99bhjz5n890yDmWVnXZNw7o+juMpCObdwxMTFh4GB3vlk4h1cHj6V9KzcGDCpO5yatmrvy5+/LmZN7AQkQEx1Hl4796dKxPx9PfnDB+dsvS2nn3JuuHQfQqnULunXvhImJCT//PJ9+/V7H0bEbQ4f2pVEjw3M2ZswwUlPTeOWVTvzyyxLmz58BwP376Xz++UKmT//SwF6lUvH993Pp2XMYzs49OXfuAu+//0ap6Ix9Z6SBjYmJyTOds5joOLp06EeXDv2Yms+XeXl//f1shg9+m06tPRgw2K1Q3sNHDSY1NY22LXqx6PeVzJr74DzFRsfTveNAunccyCdTdHG1cuVKzJ43lSF938ClrQfVa1SlW7cO/PzzfPr2G00zx64MG9qvkO/eGPMqqampvPxKR/73yxK+nD8zn+++Z/r0ouPF62Mm0Kp1L1q17sXVq9cxMTHhp5++oF+/12nevHtuXyp8nlJS0mjc2IVffvmbL7/M60spDB78Js7OPRk3bgpLl/6oTzNy5Ae0bt2bli17UL16VQYNcueHH+cxoP8YWrbo8dA+27RJZ3416LMpDB78Fq1a9eLtcR+x5O8fDdL17deTO7fvFllfhZLjhb0xEELMFUJMfbRloXTzhBDdjVQGjRBiUzHHDgshnB6WvpVzcyIjY4iOjiMzM5MNGzzp69HTwKavhyurVm0EYPPmnXTt0iF3f082bPAkIyODmJh4IiNjaOWs+3X7zh1dR1OrTTFVq2nQsC7RUbHExsSTmZnJls076e1u+EtoH7furPtnCwCe23bTqfODO/s+7t2JiYnnQtgl/b7y5cvRrp0zq1boypaZmcnNtFu0dGpGVFQsMXlam7xwc+teSOufNTqtbVu9ccnVunfvPtnZ2QCUKWNO3sf5ypcvR/v2zqxcsUGvVa9+nVLRSSvFOt26+eDjOE1avExcdAIJsYlkZWbhvW0fXXt1MtBMjE/iYmgEOTmFv8Fy+pgfdx8j4DZybIg2JpGkuCSyMrM46HmY9q7tDWySEy4TFRaNzCl+waWLWydOH/Il/X56sTaOLZsQEx1HXGwCmZlZeG7xxrV3VwMb1z5d2bjOE4Cdnnvp0Kl1oXz6DeqD52bvYnUaN9f5Thun893ubfvp0rOg75K5FBZJToE6xUbFExedAMDVy9e4cS2FylUrFav1KJwcm1CxwtN9fK2k4sMxn9PY2WlIz8gokbxvpKQWqss774xm4cI/adr0JaIiY/H3DyYzM5NNm3bg5t7DwNbNrQdrVm8GYOtWbzp31v2aGRwUSnLSFQBCQy9ibm6OmZkZDrVrEXEpmmvXbgBw6NBxxrz1mkHM27p5J70L9Nnebt1Yt3YrANu37aZjvpjX2607sTHxhF+IMEhjampKGYsyqFQqLC0tKF+hHDFRscTGJJCZmcm2LTvp7WYYW3v36cr6f3Q6O7btoWMRv5rm5969+xw/dhrQxYXgoFCsbWri7Oxo0B42btyBR74ZSAAPD1dWr9YNSVu27KJLF11fvnv3HidO+JKeft/AXgiBEIKyZXUfwaxQoRzm5malopN3LvNo4dT0mc7Zw2jesinRUXmxJ5Ntm3fRs49h7OnZpysb1upij5fnHjq4tHlonvYOtkRFxnL9egoARw+f5O1xowz77MbtRfpuld53Owv57n568TE0P3ntIW9c2rhxB+4F+pK7ew/WrNmcq7WLzp11WkFBISQV0ZcAbt3SjUOmpqao1Wrq1LEnKvLB+Ldp0w7c3Q3r5O7mmq/P7tL32aCgkCL7LEDZspaMHz+Wb7/95bHq+zyQsuS358ELe2PwtEgp50gp9xspr0Qp5eCnTa+xsSI+IVH/f4I2CY3Gqlib7Oxs0tJuUrVqZTSaItLa6NKamJjg57uXJG0wBw4c5WbaLbTaJL1tojYZa+uaBjrWmppoE5L1OjfTblOlamUsLS2YOPltFnxt2HntHey4du0Gv/75LYd9PPn51y+xtLRAo6mJNuGBllabjLWmoJaV3kandYsqVXXTyi2dmnHK15sTp3cxeeJssrOzccjV+v3PBRw7vp1ffv0KBwe7UtEpzTpZWD74EmgNq+okJz4YOC8nXqGGlfG/jFzduhpX8w3QV5OvUt266hPn07VvZw4WmFEoiLV1DZK0D76EnJx4GWvrGgY2VvlssrOzuXnzNpWrGF6YewzohecWg++9GFDTujqX8/su6Qo1rJ/cd42bv4xarSY+RvvEaY1BScUHgJpWNcjMzCqRvIuifv06tG/vzF9LFtK4SSNatGwK6PpSIV1NTRK0D/pS2s1bVK1quOykf//eBAeFkJGRQVRkDA0a1qVWLRtUKhUeHj2ws9OQmPCgrSUmFtFnrWsa9tmbt6hSRRfzJkwex3ff/Gpgn5x0md9++ZvAkMOEXDrOzZu3SEq8jDZfm07UXi4UW62sa+rjb34dgFr2thw8thXPnato07ZlIb9VqFge195dOHbkJBqNFQn5/K7VJqEpUKf8NnlaBX2Xn6ysLCZM+BQ/v71ER/vx0kv18fc/Vyo6q1duNLCxtq751OcM8ny5je27VtOmrVOBdDVIzHeekhILnydr65ok5jtPt27eokpu7Kllb8O+o5vZunMlrXPPU3RUHPXq18aulgaVSkUvt27Y2dkY9A2tNgmbQu37yXyXx+K/FnLm9G5mzJiYL5/841ISNjZPrjVgQB+CcvtSHtu3ryQuzp/bt+9w8VIUCVrDOhU8L7o++3Cd/H0WYM6cj/jf/5Zw967hTaRCyfNC3RgIIT4VQoQLIfYDDXP31RVC7BZCnBVCHBNCNBJCVBRCxAih+2a4EMJSCBEvhFALIZYLIQbn7ncWQpwQQgQJIc4IIcoLIVRCiO+EEL5CiGAhROEF5Q/K4yCEOJ/7t4UQYl1umvWAxWPUp9A+WeAWsmibh6fNycnBydkV+9pOODs1x9bO+il1JNM/ncAfvy7Tz0LkYWqqopnjKyxb8g+dO/Tj7p17TJryTrHlNdQqZKIvz1m/INo496aLywCmfPQu5uZmmJqa0szxFf5esoaO7fty5+49PPq6FpGH8XUmf/RuqdXprfGj8+VXhGZhCSPw6Lo9iio1qlCnUW3OHPF7hNTTtvcHNs1bNuH+vXuEh0UUsnsSnUdRrUZVvvplDnMmzX/itMaipOIDFHXWjZd3UZiaqqhUqSKff/Y9fn5BrFz14KL7SdvASy/VZ978T5gwXre0KTX1JpMmzmbFql/Zu38DsbFasrMLz249lg6ST2ZO4M/flheKeRUrVaB3n260bNKVxg06YGlpSdt2zk+nIyWXk6/Q/JUudO04gNmffsOfSxZSrnxZvY1KpeKvv39gyZ+riI1JeIb2UPy5MTU15e23R9GmTR9q13bi3Lkw+vfvVSo6kz4yHFqfun7ofOn4Sme6duzP7Jlfs+hvQ18Wl+7R+nA5+SotG3ejR6dBfDbzG35f/B3lypclLe0mn3z0OYuW/oCn92oS4rSFZiCLrkMhk0f2nzFjJtDSqQdduw2iQ/tWjBgx6LHyeZy+NH/+dD78cIaBTd++o6ld2xlzczMav1L4Wa5C5X0MnS/mT2f8eN2yqaZNX6ZOXXt2bP93PluQh/KMwb8cIURL4FWgOTAQyIvIfwHjpZQtganA71LKNCAIyHsqzgPYI6XMzJefGbAemCilbAZ0B+4BbwFpUkrnXI1xQojaj1HE94C7UsqmwJdA4Z9/dLpvCyH8hBB+8fFR2Nlq9MdsbaxJSrpsYK9NSNLbqFQqKlaswI0bKWi1SYXTJhqmTUu7yZGjJ7C3t8XG5sHNgcbGiuRkw2ncRG0yNrZWep0KFcuRciOVlk7NmPvFNALPH+Ld98cw+aN3Gfv2SBK1ySRqkznrFwSAp+dumjq+glabjI3tAy0bGyuSC9QpMZ+NTqs8KTcMlx9cDI/kzt17vPxyQ7TaJLT5tbZ5U9OqRqnoNGtWenV6ucmDAHw56QpWmge/ptfU1OBq8lWMzdWkq1TP96t9davqXEu+/kR5dPFw4dju42RnZT/ULinxMtb5ftGy0tQkuUCd8tuoVCoqVChHakqa/njfgb3Z9pBlRKCbXamZ33fWNbiafO2x61O2nCW/rV7IL9/+RbB/yGOnMzb5+z4YNz4kJ19BrTY1PG7E2FNUXbZ77karTaKMuTk5OTlUq1YFGxurwrraZGxtHvSlihXKcyO3L2lsrPhn3SLeHvsR0dFx+jTeuw7QxWUA3boM4tKlKKIiY9DYPmhrGo1VoaUriYkF+mwFXZ9t4dSMz+Z9jP+5g7zz3utMmvoub709EpfO7YiNTeD69RSysrLw2rEXK01Ng19pNTY1C8XWpMRkffzV66SkkpGRSUrusqvgwBBiouOoW+/BUPPDz18QFRnDoj9W5PolCdt8frexsdYvB3nguwc2eVo3bhRe2pVHs2YvAxAVFQvA5s1e1KplUyo6zq1bGNgkJiY/9TnLyMjUx9ugXF/Wy+fLxMTLBrNa1pqaReatyXeeyhd1noJCiY2Jp25dBwD27T5Mn+6v4u76GhGXorl0Kdqgb9jYWJNYVPt+At/llQ3g9u07rFu/DWcnx9x88o9L1iQmFtQq/jzZ2Fixfv1fjB07xaAv5ZGeno6X1z4aNqqHrY1hnQr5Tpustymoo7GxYu26RYzLp9OqdQuaN29CaJgP+w9spF792njvXvdQHygYjxfmxgDoCGyVUt6VUt4EtgNlgHbARiFEILAIyOsp64FhuX+/mvt/fhoCSVJKXwAp5U0pZRbgCozOze80UBWoz6PpBKzOzSsYCC7KSEr5l5TSSUrpdPZsOPXq1cbBwQ61Ws3Qof3Y4WX4IOkOr72MGjUE0L1549Dh4/r9Q4f2062xdbCjXr3anPENoFq1KlSsWAGAMmXK0K1rRw4dOkGdug7UsrdFrVYzcJAbu3cavjXEe9cBXh0+EIB+/Xtx7MgpANx6DsexcRccG3fhz9+X8+PCP1ny12quXLmGVptEvfq64Ovi0pbwCxH4nw2mbl0H7PO0Bruza5eh1q5dBxg+QqfVf0Bvjh45CYC9va3+wVw7Ow3169cmNi6hsFbndvieDigVndKsU+TFaH1+5wPCqFXHDpta1piqTendvweH9hzD2IQHhWNb2wYrOytM1aZ07deZE/tOPFEe3fp15YDnw5cRAQT5n6d2nVrY1bJBrTal38De7Nt9yMBmn/chhrzaDwC3fq76tdag+/XLvZ8r27c8/MYgJDAM+3y+69W/O4f3Pp7vTNWm/LTsW3Zs9GbfjkfXqSTx9Qs0enzII/hcGOa5x4ydd1F4bt+DS+d2nD0bTKOX6mFhUYa0tFsMHuzBrp2GKzt37drPiJGDABgwoDdHcvtSxYrl2bx5KXPnLODUKcOH3PPe0lKpUgXGvT2SH7//gzp1HsS8AYPc2F2gz+7edZBXXxsAQN/+vTiWq+PRazgtmnSlRZOuLPpjBT99/yd//7WahIREnJwdsbDQLfnr5NKWU8fPUDtfbO0/0I3duw4W0hk2XKfj0b8nPkd1sbVq1cr6h7btHWypU9eB2Jh4AGbMmkSFiuX4dPpX+nz8/IIM2sOQIR54eRk+PO/ltY+RI3WrWwcO7MPhww/vy4mJl2nUqD7VqlUBoFu3jpw+HVAqOpfCIw1sAs6ee+pzZuhLO+rUdSAm15cAgf7nqFPXnlr2NrrzNKgPe70NY89e70MMfU0Xe9z79eR4Eeeplr0ttevYExujew4prz4VK1ZgzNjX+PbbX6hXz+FBvxrSt0jfjdL7zo3Duf2qOFQqlX5ZjqmpKX16dyMkJFzfHuztH5ynnTsNtXbu3M+IEYNytfpw5MgJfXm3bFnGnDkLOHnywUxv2bKWWFnV0Ov26tWF48fPULfeg/Fv8OAidHbty9dnC+hsXsZnBfrsksWrqVe3NS+/1IHu3YYQcSma3r0KvxHvefOizhi8aB84KzjfZgKkSikdi7DdDnwthKiC7tf7gqO8KCK/vP3jpZRPM8f1RGsOsrOzmThpFrt2/oPKxITlK9YTGnqRuZ9Nxe9sEF5e+1i6bB0rlv+PC6E+pKSkMnyk7vVnoaEX2bRpB+eCDpGVnc2EiZ+Sk5ODtXVNlv79EyqVCSYmJmzatIPduw6QlZXFpm1LUZmoWLNqExcuRDDj04kEBJxj966DrF65kT8Xf49f4H5SUlIZ+8bkR5b/k6lfsGjJQszM1MTExPPhe9PJzs5m6kefs2XbclQqE1av2sSFsEvMnDWJAP9zeO86wKoVG/hryUICgg6SkpLKm2N0aybbtHVi8kfvkJmZhczJ4aPJn3Ej98GuaR99zpK/f0RtpiYmOp4P3pvGkSMnS0WntOr01UcLDNrGVzO+Z9G6n1GpTNi61ovI8Gg+mDaOkKALHN5zjMaOL/HTsm+pUKk8nV078MHH4+jvMhyAFZ5/UruePZZlLdgfsJ05k7/kxOEHF9kPdHL4efYvfLfmG0xMTPBev5uYi7G8MfV1woMucmLfSRo2a8j8JXMpV7EcbXu0ZcyU13mjm+51f1a2NamuqU7QySLvgwu199nTvmLNpkWYqFSsX7OVixcimTrjA4ICQti3+zDrVm/h5z+/xsdvF6kpabw/9sFbR9q0cyIp8TJxsQmP1Plq5kL+WKvrB9tyfff+tHGEBoZxeK8Przi+xE9Lv6FCpfK49OjAex+PZaDLCHr27UaLNo5UrFyBvsP6ADB74nzCQy49VLM4Pv7sG3wDgklNvUm3/iN5/61RDCrwkO/D6mHs+ACwetVvuHRqi4mJCWEhPqSkpvLLL38bNe9q1aoQE+XH5/O+Z9nydbptyU+cPLWT9PQMypibczZgH6tWbiQs7BKzZk/G3/8cu3buZ8Xy9Sz5+0eCzh0iJSWNMaPHA/DOu69Tp649n8wYzyczdPv6eYzm6tXrLPhuDk2avATAN1//j4vhUUz/eB4bt/6NiUrFP6s2EX4hgumfTiDQ/zy7vQ+yZuVGfv/rO84E7iM1JY1xj4h5/n7B7PDcw8Fj28jKyuJccBjLl64jKjKWDVuWYKJSsXb1ZsIvRPDJzAkEBpxnj/dB1qzapNMJ2EtKShpvv6nTadvemU9mTiArK5ucnGymTv6M1JQ0rDU1mfLxe1wMj+TgUd2Dtn8vXs0fi1cxadJsduxYhUqlYsWK9YSFXWTOnCmcPXuOnTv3sXz5epYu/YmQkKPcuJHK6NEf6ssfHn6c8uXLY2amxsOjJ+7uI7lw4RJffvkT+/dvJDMzi7g4LePGTeHgQZ8S15n0wcxC7f1pz1nb9s5M/3SizpfZ2UydNMdgpjE7O5uZH89n7eYlqFQmrF29hfALEUybOZ7AgPPs9T7EP6s28euibznpv5vUlDTeeVP3mtg27Z2YNmMCWdlZZGfnMG3KXFJTdXl/8c1MXsl9bfLCBX9wITyCSZNm47VjNSqViuV6332E/9lgvHbu0/WFpT8RGnKMGzdSGTX6wauCw8NPUCGf79zcRxAXl4DXjtWo1WpUKhMOHvTh76X/gITJk+ewY8fK3PO0gbCwS8yePQV//2B27tyfe55+5Pz5I6SkpDJqlO48vfvu69St68D06eOZPl3Xlzw8RiGEYNOmJZiZmaFSqThy5AR/LVpFVGQMntt1OitXbiiiz25gyd8/EHzuMCkpqbyu77OjqVPXnukzJjB9xgQA+nqM4urVJ5uVVjAu4nmtjzU2QogWwHKgNbobHn90MwQDgR+llBuFbkFdUyllUG6ajcB94JaU8v3cfcsBL3Q3DheAYVJKXyFEeXRLid4E+gBDpJSZQogGgFZKeaeIMjkAXlLKxkKIKcDLUsqxQojGQCDQRkpZ7MJrUzObUjk5FcwtS0MGgOwX9VOBpYBdWeM/XFwU1dRP//rNJyXibvKjjYxAFbOne/PPk3L2/JpS0QGw0HR8tNF/iDKmZqWopS4VnaLWcJcUt9LvlZpWaVDOrMyjjYyEqYmqVHRS7t9+tJGRMBGlsyDEpBTb+J27Mc/nJ/RiiG7Wo8Sv0WoH7Sv1Or8wMwZSSv/ch3oDgVggb23ACOAPIcQsQA2sQ/d8AeiWD20EOheRX4YQYhjwixDCAt1NQXdgCeAA+OfeaFwF+j9GEf8AlgkhgnPLeOYpqqmgoKCgoKCgoKBQIrwwNwYAUsov0T3YW5DCr1HQ2W+iwAs4pJRj8v3tCxT1suKZudujyhMDNM79+x66ZxkUFBQUFBQUFBT+wzyvZwBKmhfp4WMFBQUFBQUFBQUFhafkhZoxeF4IIZoAqwrsTpdSFv4sq4KCgoKCgoKCwn8aKV/MGQPlxsAISCnPAUW9+UhBQUFBQUFBQUHhP4FyY6CgoKCgoKCgoKDwBLyoL1lUbgwUuJl+93kX4T9LaVm4ca0AACAASURBVE4kXsiIf7TRf4zS8l8yKaWiU5qvEL2XaPwP2hVFadXpflZGqegApJeS1ovxMvDnQ+r9Qm8AV3gCsnlBr1r/ReS8oEuJlIePFRQUFBQUFBQUFBSUGQMFBQUFBQUFBQWFJ+FFffhYmTFQUFBQUFBQUFBQUFBmDBQUFBQUFBQUFBSeBOUDZwoKCgoKCgoKCgoKLyzKjIGCgoKCgoKCgoLCEyBf0NeOKTMGCgoKCgoKCgoKCgrKjcG/lF5A+IVQH6Z9/EGhg2ZmZvyz5g8uhPpwwmcH9va2+mOfTPuQC6E+hJw/imsPF/3+xX8tJDEhiIhLpwg5f5T8eX/w/huEnD9KUOBBvlsw+4nz7unauVCeADu91nD7VhR3bkUT4H+AsmUtAVj43Vz8fPdy1m8fKdfDSb8X98xaXTq358zp3URcOsX1qxcIDzvOtI8/wKVTW65fDcPPdy9+vnv5bM5HT1Q/c3NzTh734qzfPoICD/LZnI/05bhx7QJ3bscQHx/A4r8WYmr6YALOzMyMNWv+ICzUh+MFdKZN+5CwUB/Onz9Kj3x1AzAxMcH3zB62bV2h37dv7wbu3I7mzq1oTp3cZaDzNO3B1lbD/r0bORd8mKDAg4z/8K0Hdboezp1bUcTF+hNx8RR+vnufWgcetLvAgAMGZZ437xPu3IomIz2Bn378goI8jf8uXTxFgP9+/Hz3curkrkJ5/vnHArIytFwKP2mUfvWwtlFUGy0JPz4us776gU5ur9J/5LuPnUaoLTCtZGu0ehRsd/M+n6bvl4kJQaTfiycu5iybNi6hYsUKADRsWBefo9u5cyuKKZPfeaq6F+fThPhAbt+K4vatKKKj/Iqs39O2wfALJ7h1M7LEfJfXZ0HX3rQJgdy9HYM2PpBvvv70mbSg+PGiadOX8Tm6nQD//WzbupyqVSsbbbx4/70xXAj1IStDy4VQH4PjLp3a4ue7l6DAgxw6sNlovlux/H/cuxOrj3m9e3V9Jt89LCZcvxrGnVvRxMf5s37dX/rx8FnPUf6Y0NO1MxGXTnH7ZiRxsf6cOrkLZydHo+sArF+7SD8uBQUe1PfZktCaM3sKsdF+AIG5Wx/+BcgcUeLb86mYlMr279pUUspIKWWdMpb2MjAoRDZu6iJVao1+++DDGfLPRSulSq2Rr414V67f4ClVao1s3NRFBgaFSIuyDrJu/dYyIiJaqs1tpUqtkZ27DJCtWveS6enpsl6DNjIv7zfenCT37z8qLco6SJVaIz+ZMf+J8lab28qIiGiDPBs3dZFqc1sZFRWr33/lyjX544+LCtXDx+e0XLps7TNpmZrZyLg4rXy5cScZEREtf/n1b/nOux/r6vfGROnlte+ZfFehUj2pUmukuUUtefr0WdmhY18ZEREt3xo7WVpY2sugoBC5c9d++cEH06WpWiNN1Rr54Ycz5KJFK6WpWiOH5+qYqjWySVMXGRQUIi3LOsh6uTpm5rb6dFOnzpX/rN0ivbz2SVO1RpqZ28rExGRZP7fON1JS5bwvfnim9mBj5yidnF2lSq2RFSvXl+EXI2VTxy6FfLt8+Tr52dwFz9zunJxd5bnzYfp81Oa2Mi4uQfboOVQeOXJCXrwYKZs0ddH74Gn9Fx0dJ2tavWKQT95Wu24reefOXZmQkCht7JoZrV8V1zYKtlFj9N+Cfsy4GvnY24l922Sgzx7Zp2ePx06Tk5UhM67HGq0eRbW7vDz7uL0mk5Iuy9p1neWC736VC777VarUGmmlaSJbt+ktv/r6Z/nxtM8N9B9nK64sZua2MiMjUzq36qnvw8Zqg9aaJjIiIlrfZ0vSd2pzW6nVJkkfnzOyQqX6MjAoRHZy6Vdi40XwuVDZpetAqVJr5FtjJ0tv7wNGGS9Uao1s6dxD1mvQRn9e8o63becmQ0LDpUMdp6caox7mu+vXU+TX3/xs1L5aXExo1ryrXmfFivVyxswvjRoT8nx77Ngp2a//aBkYFCLfe3+aPHz4eInE8MTEZNmwUXtZxtJeXr58Vf69dE2JxDmVWiM/n/e9/Hja5/JfcH1msIXU6SNLense9XphZwyEEHOFEFOfIt08IUR3I5VBI4TY9ITJWgERQFRmZiYbNnjS16OngUFfD1dWrdoIwObNO+napUPu/p5s2OBJRkYGMTHxREbG0Mq5OQDHfE5jZ6chPSOD6Og48vKePOltFnz3GxkZui+Bdu3c/onybuXcnMjIGIM8+3r0pJVzcy5ditLvj4qKpdFL9QvVo0KF8qxfv+2ZtKpWrUx6ejqVK1UkMjKGTZt20K+vLo927Z2f2Xd37ui+DK1Wm2KqVvNSo/pERsawfMV6MjMzWb/BE6TExtZar+NRjI6HR0/WF6NjY2NN797dWLp07YPG4Nycc+fC9HU+ccKXjh1aP1OdkpOvEBB4HoDbt+9w4cIlunZuX8i3/fr1Zt16z2dudzdSUg3K28q5OWFhlzh40AcpJfv2HcGjQBt/Gv89jL+X/EBQUAiZmVlkZmYZrV8V1zYKttFn1SnKj0+Ck2MTKlYo/9j2wtQcmZ0JOVlGq0dR7c5GYwVATo4kKiqWuDgtp077Y2Oj60tXr17H72wQmZmZhco4fPhATh73ws93L7//9i0mJoWHs4fFkqysTOLiEvR92FhtsHnzJkZvA8X5rpVzc0xMTJj3xULu3LnDhg2edHjG+ADFjxf169Xh6LFTAOw/cIwOHVobZbwACAwMoWaN6mRlZRKbe142bPBk+ifj2bbNm/j4RODJx6iH+S4lJZUbN1KN2leLiwnnz1/Q6zRsWA8p5TPpFIwJeb69e/ceFpaWbNjgiYtLOxKTLhtVJ0/r3LkwIiKjyczMZO++I7Ro0dQo7e5Z4lxpkyNFiW/Pgxf2xuBpkVLOkVLuN1JeiVLKwU+YzAaIz/snQZuEJnfwzENjY0V8gi5IZmdnk5Z2k6pVK6PRPNivT2vzIG1NqxpkZmYZHLeyrkGHDq044bODg/s3UbeuwxPlnb8s+cubt3/J4h/QxgdSoUJ5YmP11QLA3sGOGjWqcfDQ8WfSunbtBmq1mo4dWhOfkMjAgW7Y2mlI0CZRrWoV2rRpyVm/fXhtX0WdOvZP7DsTExP8fPeSpA3mwIGjpN68aWCblHQZZ+fm7Nlz6JHnyEZjRUK+tNp8OgsXfs6MGfPJyckxyCfP3tTUlFdebkhKgcD5tO0BwN7eFsdmjbmRkmZgW7asJRkZGURERBtFp7jyAly5ck1/gfgs/pNS4r1rLadPeTP2rRF6G3f3Hty7e4/QsIuGZTRCv3pU2zBm/y1VTEwhxzBWGLMeee3u9JkAAIYO7ce69dsAeGPMq+zO15eKolGjegwd0peOLv1xcnYlOzub4cMHFrJ7WCzJysrWt5d6dWsbrQ3++stXtGjRVN8GS9J3Ghsr1Gq1PoaPGjkYR8fGRtEqarxITU3Dw8MVgMGD3LGwKGOU8SJ/WbOysg2O29vbUqlSRQ7s28jpU968/HJDo/ku7eYt3n/vDfzP7qOnaxdq1671zL57WExYsvgHpn38Aba21vz629JnPkdFlXXK1M/49utZTJn8Lm59uvPprK+NqlMwH4BXXmnI1as3ntl3D+P9994ACAaWApUfmUDhqXmhbgyEEJ8KIcKFEPuBhrn76gohdgshzgohjgkhGgkhKgohYoQQJrk2lkKIeCGEWgixXAgxOHe/sxDihBAiSAhxRghRXgihEkJ8J4TwFUIECyGKXfgqhHAQQpzP/XuMEMIztyzhQojPikrzww8/9Fi/fn0/IYRfTs4dAINfFnLzKpROyuL2P0hb1L2niTChUqWKtOvgwSfT52Nnp3mivB+1f+y4KdjZtyAxMZl6dWsb2FWqWIFd3gcMLoSfRgtgxMj3GT16KH09XLl9+45+cLly9Rp16rWipVMPfvt9GXZ2Nk9UP4CcnBycnF2xr+2Es1NzahXI4/XRQ0lMTOb48TP6fU96jvr06c7VK9fwDzhncCy//a+/fEX4xUi0icnF2jxunUB38b9h/WKmTP2M++npBnatW7fk4qUoo+gU5HHsn0bLpXN/WrXuhbvHSN57bwwdOrTGwqIMM6ZPYOOmHSWi+ai2YSydfwPGqkf+dnfr1m3UajUe7q5s2uzFjOkTyMrK4p9/tjy0LF27dKBF8yacOrkLP9+9dO3agToFLuqKL6Mulnjt3KdvL926dcTKuuYz18+lc39mzPyKvXsP8957Y/SzeyXlOyEEwkToY/j6DZ649uhsFK2ixosDB4/x/rtjOH3Km/Lly1JU83zaGF5cWYUQtGzRFI9+o+njNpzq1asWuoB/Wt9duHCJBo3a0dLJlbS0m7RrZzjDbOyYMHbcFCZNns2NG6kMHdL3mXQKkmf7ztuj+ejjuUyZ+hk+x8+weNFCo+oUzGfG9AnkZGcTHh5RrM2zaAH8uWglDRq1A3AEkoCFD01QSkgpSnx7HrwwNwZCiJbAq0BzYCCQ18P/AsZLKVsCU4HfpZRpQBCQ99SLB7BHSpmZLz8zYD0wUUrZDOgO3APeAtKklM65GuOEEIZXvMXTChiBrnEPEUI4FTSYMmXK8mHDhvlLKZ1MTMpia2NNUr6pQABtQhJ2troLeJVKRcWKFbhxIwWt9sF+QJc28UHa5OQrqNWmBsevX7/Btm3eAPj6BZKVlU3jxo0eO+/8ZdHvTzLcn5OTQ1R0rH55QB4WFmU4fdr/mbUATp0+y7i3PyIg4DzHjp0iIiIaWxtrYmMT9FO73rsPkpOTTeNXGj6x7wDS0m5y5OgJHBzs9LazZk2mevVqbNy4/bHOUYI2Cdt8Oja5Ou3aOeHu7sqli6dYs/p3unRpz4rl/0OboLPX6VTl6NGTRmkPpqambFy/mLVrt7Jtm3ehPFo5Oxrc6DytTlEUPI81alQzmO5+Gv8Ber9cvXqdbZ7eODs7UreuAw4Otfjqy5kMf20AtrbW+J7eQ6OG9YzWr6DotqG3NaJOqZGTpZs1yF+WEmh3AL16dSEg4Bw9e3bBrU93Ro3+8JHFE0KwavVGnJxdcXJ25ZXGnZj3xQ/069dL/0BzyxZNHxpLqlbR/eh49ep1LkVEYVHG/LHq96g2qE1Iolq1Kvo2WJK+0yYkkZOdo/8/IyOTrKwsqlWr8kxaUPR4ERp6kd5uw2ndRrfM8M6dO0+U98NieF5ZTU1VhY7v2XuIu3fvcf16ClevXdcvl3pW31WrWoWcnByklFwIj6BKlUrPfJ7yKC4maDRWnDp9loED3IyiUzCP0aOGsHXrLmxtrDl27BTOzo6FbJ5FJ38+o0YNwa1Pd3Z47S3ROHflyrW8HxBzgMXorqUUSogX5sYA6AhslVLelVLeBLYDZYB2wEYhRCCwCMi7Ol0PDMv9+9Xc//PTEEiSUvoCSClvSimzAFdgdG5+p4GqQH0ej31SyutSynvAFqBDETa+ufnVVqvVDB3ajx1eew0MdnjtZdSoIQAMGuTGocPH9fuHDu2HmZkZDg521KtXmzO+Afp0wefCMM89lpf3+g2edOnSHoD69euQnp6uX2f5OHn7+gVSr15tgzx3eO3F1y+Ql16qr9/fv18vTp8+qy9LgwZ1yczMonnzJs+sBVC9elV8/QKpX78Os2dNYenSfxg6tB8nTj5424izkyP37qXTt2+vx9asVq2K/m0LZcqUoVvXjhw4cIx69Wrz8dQP6Onahezs7ELnyKuYc+TltZdhRejMmvUNtes4Ub9BG0aMfJ9Dh47z+pgJ+PoF0rx5EzzcXRnzxiSjtYfFfy0k7EIEP/38l67R5fNtr56dEUKw5p/NRml3BcmvJYSgRw8XvJ7Rf5aWFpQrVxYAS0sLenR3ISQknPPnL2Bj2wyHOs4kJV0hOfkK7Tq40Sd3MHuW+j2sbRTVRo3tx5JEZqUjVGowMTVqPQq2O4BXh/XnfMgFPp76Pv0HjuHevfuPLN/BQz4MHOBO9epVAahcuRK1atng6blbf7Nw1j+42LKEhIbToEFdHBzsqFixAm1at2T7jj0GGk/bBn39AmnQoA7ubj0ID48oUd/5+gUCkgH9e6NWqxk1aggZGZlcu3bjmbSg6PHCJ/fHAiEEM2dMxMtr3xPl/bAYnlcfU1M1texs9Md//3M5Hdq3RqVSYWFRBhMTQbOmLxnFdw0b1dOXZcTwgQQEnH+m8/SwmODSqa2+TmZqtcEv7MaICXm+vXrtOt26dmTo0H5cuXKNS/mWgxozhjdt+jIzZ0xgyLCxDBjgVqJxzsqqRv5/BwDnizEtVaQs+e05Vez5P9ltjA2YBHye7/8fgDnoLu6Lsi8HxAJVgDhAlbt/OTAYaAr4FJFuM9DzMcvkAJzP/XsMsCLfsXnoZiOKSttHSnkxIiJazpr9jVSpNfKL+T/IfgNelyq1RlqWqy03btohL12KkmfO+Mt6Ddron96fNfsbGRERLS+ER0g39xH6/WvXbZWJickyMzNTZmRkystXrspZs7+RZSztZXBwqIyJjZdn/YNl7z7Dnzhvd4+RMvxipMxfXlMzGxkSEi7v378v09PTZWDgeVmpSgN9PT6f9738fuHvRtFSqTXy++9/l6FhF2V8QqK8fOWq/vj4CTPl5StXZVR0rDx16qzs2m3QE2k6tugm/QPOyaDgEHnufJj+LT3uHiNlTk6OzMjIkImJyTIw8Lw8fPi47D/gdWmq1siyBc5R/QZt9G87KahT8A06XbsN0r+VyFStkVlZWTI9PUPev58uExOT5WdzFzxTe+jk0k9KKWVQcIgMCDwvAwLPS3ePkXrf3rx5S3p67jZqu8vIyJDx8Yly7LgpUqXWyPlf/igzMjJlTk6OvHXrttyz55D8Yv4PT+2/+g3ayKCgEBkUFCLPh1yQs2Z/Y+DTvHOWkZEho6PjjNKvHtY2CrbRkvDjk7yVaOL742S7tq3lyy+9JDu2byvXLv39kWkyUxNlTla60epRVLsbNOhNee3aDRkZGS3j4rQyIPC8jIvXyiNHT0qVWiM1ts1kfHyiTEu7KVNSUmV8fKKsVKWBVKk18tXh78qAwPMyKDhE+p0Nku3auxf5ZqKiylK/QRsZFRWrj0/79h2Rprn1M0YbjImNl1evXi9R37l7jJQqtUb2G/C6TEu7KdPT06VWmyS79xhSYuPFpMmz5bVrN2SCNkl+u+CXp8q7uBg+cdIsGR+fKLOysmRmZqZMS7upP75v/xEZG5cgz50Pkx9Pm2c03x046CPv378v799Pl2FhF6WNnWPJxIS+o+Tdu/fk/fR0mZx8Ra75Z7P8dsGvRo8J7h4jZVxcgrx//75MTLosT58+KxcvWV0iMVyrTZIZGZn6cenPRStLbLxYtXqTDD4XKqWUwVLK7VJK6+d9zSmlJMjeXZb09jzqJXIvUv/zCCFaoLuob43ui87+6GYIBgI/Sik3Ct3itqZSyqDcNBuB+8AtKeX7ufuWA17oZhwuAMOklL5CiPLolhK9ie4dukOklJlCiAaAVkp5p4gyOQBeUsrGQogxwFdA49x8TgNvSikLv0A7F1Mzmxfj5LzAlOYKwBexMZSW/15E391LPFYqOhaajqWiU5oo7U5B4b9HVob2Ob3Yv2gC7fuWeBd3jN1e6nU2fbTJfwMppb8QYj26j1/EAnmj5gjgDyHELEANrEP3fAHolg9tBDoXkV+GEGIY8IsQwgLdxXx3YAm6mQD/3BuNq0D/xyymD7AKqAf887CbAgUFBQUFBQUFBYXS5IWZMfi3kztj4CSlfPSTdbkoMwb/fpQZg2dD+eX26VFmDJ4epd0pKPz3+LfNGATU6lfiXbx5nGep1/lFevhYQUFBQUFBQUFBQeEpeWGWEj1PhBBN0C0Ryk+6lFL/CUop5XJ0z0AoKCgoKCgoKCj8h3lRF9woNwZGQEp5Dt23CRQUFBQUFBQUFBT+kyg3Bv9iSmthmV2FGo82MhJ3Mu+Vis7tzEe/C91YZOf7cnNJYqYqne6akZ1VKjoAspRWYeeU0jkqzR+QSmvtf2k9ywDQoOGAUtGJv3WtVHTKmJqVig5AelZGqegU9eXaksBMpS4VHYAypqWjlXa/0MsLSwyVierRRkbR+f+7Ij3nOX2ZuKRRbgwUFJ6B0ropUFB40SmtmwIFBQUFYyBf0BuD/7+3egoKCgoKCgoKCgoKepQZAwUFBQUFBQUFBYUn4EVdSqTMGCgoKCgoKCgoKCgoKDMGCgoKCgoKCgoKCk/CC/q2UmXGQEFBQUFBQUFBQUFBmTFQUFBQUFBQUFBQeCKUZwwUSpNeQHhYqA8ff/xBoYNmZmasWfMHYaE+HPfZgb29rf7YtGkfEhbqw/nzR+nRw0W/v2LFCqxb9xfnzh0hOPgwbVq31B8bPfZVjgfv5oL2NAERR3h3whtFaKr535JvOHjGky17VmJjZw2Aqakp3/06D++jG9h7YjPvTXwTgNr17PE6tE6/BUUf4413hgPQpVsHjvt5cypgD+MnjytS669lP3AqYA/eB9ZjV8sGALtaNsQkB3Lg2FYOHNvKgh/nAlC2XFn9vgPHthIadZIFC+bQo4cLAYEHCD53mI8+eq9IP65Y+SvB5w5z+Mg2atXS+bFr1w74HN/BmTO78Tm+AxeXtvo03rvXERB4gJOndnHy1C6qV68KQI8eLgQHHyIk5ChTp75fpNaqVb8REnKUo0c99eesSpVK7NmzjmvXwvjxx3l6+3LlynL6tLd+S0gI5JsFs+neoxNnA/YTGHyQyR+9W6TOshX/IzD4IAcPb6FWru9atmyKz0kvfE56cfzUTtw9XAEwNzfj0JGtHD+1k9O+u5n56aQSqQ/A0KF98fPbi6/vHrZvX0nVqpUBcO3RmXPBhwkNOVas1upVvxMacoxjR7cX0FrP9WsX+OnHLwqlAzh6xJObaZEYsy9duniKAP/9+Pnu5dTJXbo6uHYmOekcd25FExfrj/fOf7C2rmmg88+aP7gQ6sOJAjqfTPuQC6E+hJw/ims+ncV/LSQxIYjAgAMGZe7p2hltQiB3b8egjQ/km68/LVSnJ9GytdWwf+9GzgUfJijwIOM/fEtv/+3XszCtZItpJRtU5WuCePSQMeurH+jk9ir9RxZun49Dp67tOHDak0O+O3g3N54Y1k/NL0sWcMh3B1v3rsbGTgPoYtH3v32B97FN7Du5lfcm6dJ++7/PibjizwXtGXYeXo/ngX8M8vtoyrv4+e7Fz3cvgQEHSL8XR+XKlZ6ozMWdw5CwY4SEHuV6ygWu3bjAlGL67IqVvxB07hCHjmzV99kuXTtw7Ph2Tp/x5tjx7QZxaMgQD06f8ebUaW+O+ngSdO6QUdt4UeOFq2tnzp8/SmioD57bVpCRnqDvw3qd1b8TGuqDz7ECOh9/QGioD+fPHTHQmTBhLIEBBwjw38+qlb9ibm5uUPbvF87l6vUw/AMPEHTuUIn4b6vncqpUqWyQZ9fuHTl1djdnAvcxYfLbRWiqWbLsJ84E7mPPwY0GY1T85WAO+XhyyMeT73/8vFDaPD+WdEyC0hmXSmKsLVeurH6MPXlqF7Fx/ixYMKdQvgolhJRS2f5dm0pKGSmlrGNhaS+DgkJkk6Yu0lSt0W8ffjhDLlq0UpqqNXL4iHfl+g2e0lStkU2ausigoBBpWdZB1qvfWkZEREszc1tpqtbIlSs3yLff/kiaqjXSwtJeVq3WSJqqNbJb98HS5/ApGRsdLzu1cJNtGveQoefCZY+2A2Xtqo76bfbUL+WaZRtl7aqOcvzYT+SOrbtl7aqOcuLb0+X2Lbq/X7JtI+NjtbKDY2+DtHWrt5BXkq/K9s16S6tKL8noqFjp3LSbtKnaWJ4PDpMdnPvIGhUa6rdpU+bK5X+vlTUqNJRvvzFZbtu8U9ao0FC2bNxVhoWEG9gWtQUGnJc9XYfKyMgY+fJLHWTFCvVkcFCobNG8m7S0sNdvEyd+KhcvXi0tLezl6FEfyo0bd0hLC3vZtk0fWaeOs7S0sJdOLXtIrTZJn+bIkZOyfXt3/f/m5nbSwsJeRkbGyEaN2sty5erIoKAQ2axZV2lubqffxo+fKf/6a5U0N7eTI0e+Lzds2C7Nze1k5coNZJcuA+UHH8yQv/++zCBN/u3s2WDZu+cwGRUZI5u83ElWqdhABgeHSqcWPWR5y9r6bfLE2XLJ4jWyvGVtOWb0eLlp4w5Z3rK2rFH1JVmpfD1Z3rK2rFenlbxy5ar+f6vqr8jylrVl5Qr1pe+ZAOni0t/o9bG0dJCXL1+VGk1TaW5uJ7///g/5xRc/yDIWtWRkZIxs2KidLFuutgwKCpFNm3WRZua2+k2ntVKamdvKEblaZua2slLl+rJzlwHygw+my99/X2aQxszcVg4dNk7eunVbhodHSmP2pejoOFnT6hV9HmbmtjIiIlo6Nu8qy1jay8CgEPnV1z/LPxetlCq1RqrUGvnBhzP0/7+Wq6NSa2Tjpi4yMChEWpR1kHVzddTmtlKl1sjOXQZIJ2dXee58mD4ftbmt1GqTpI/PGVmhUn0ZGBQiO7n00x9/Gi0bO0fp5OwqVWqNrFi5vgy/GCkbN3WRKrVG9ur9qsy4GikzrkbKrDspMutOiv7/4rYT+7bJQJ89sk/PHo+0zb85VGkq61RzlDFRcbJj896yfs0WMvTcBdm9bX/pUKWpfps1db5cvXSDdKjSVH741jS5Y8tu6VClqZww7hO5fbO3dKjSVDayaSXjYxNk+2a95FC3MTI58bK8FB6pzyO/v/Jv/fq/Lg8e9Cn2eFHbw85hTEy8jImJk6+81FFWqlBfBgeFypbNu8uyFg76bdLEWXLJ4tWyrIWDfH3Uh3LTxh2yrIWDbNumj6xbp5Usa+EgnVu6Sq02SZa1cJAVytWVVy5flbVsm8vyZevIlJRU+duvfxu1jRccL6rXeFlGRETL+g3ayAYN28ibN29JrTZJWlk3lmozG6k2s5Efjp8hF/21UqrNbOSIEe/JDRs8pdrMLGt+pgAAIABJREFURjZt2lkGBYXIsuVqy/oN2siIyGhpXsZO2ju0lFHRsbJ8hbpSbWYjN27cLt98a5I+vw7tPeTaf7bI7OzsEvNfWQsH+cPCP+W3X/1PVi1fX1YtX19Wr9hQRkXFyhZNukqrKi/Lc8Fhsq1TL/3xquXry6mTP5PLlvwjq5avL8eOmSS3btopq5avLx1f6SxDQ8INbPNvebGifoM2JRqTTNWaUhuXSmqszb/5+wfLHt2HyH/B9ZnB5lNzkCzp7XnU67nPGAgh5gohpj5FunlCiO4lUaZnRQhx+xlsWgERQFRmZibrN3ji4dHTwMDDw5VVqzYCsHnzTrp26ZC7vyfrN3iSkZFBTEw8kZExtHJuTvny5ejQoTVLl60FIDMzk7S0mwC8885o9nsfJiYqjvhYLZeTruK1dQ89enc20OzeuzOb1+0AwHv7ftp1bAWAlGBpWQaVSkWZMuZkZmZy+5bh1x3bdWpFbEwCiQlJtGjZlOioOGJjEsjMzGTbll30cutmYN+rTzc2/LMNgB3b9tAh3y89j6J2HXuqVatCenomUZGxxMTEk5mZyaZNO3B3dzWwdXdzZc3qzQBs3bqLzp3bARAUFEJy0hUAQkMvYm5ujplZ8V8wdXZ2JDIyhujoODIzM9m4cQceHoZaHh6urF69CYAtW3bRpUt7AO7evceJE76kpxf/pea6dR2oUaMqGemZREU9qNPmTV64ufcwsHVz787aNbo6bdvqra/TvXv3yc7OBqCMuTky31NTd+7cBUCtNsVUbUqjRvWMXh8hBEIIypa1BKBChXIkJV0u5LsNG7cXqbVKr7WzkNb99PRCPitb1pJPZ04iODiUzMxMjNWXiqKVc3MiI2M4f/6Crg4bPGnRoikyn5P7FqPT16MnG4rROeZzmhspqYW0TExMmPfFQu7cucOGDZ506NDawOZJtZKTrxAQeB6A27fvcOHCJWw0VgDs239Un6/Muo94jK+pOjk2oWKF8o+0K4pmLRoTGx1PfKyWzMwsdmzdXSgW9ejdhc3rtgPgvX0f7TrlxSKJpaXFg1iUkcXtW7c5c9L/sb98PWxYP9at36b/f/jwgZw87oWf715+/+1bTIr4yuvDzqGZmRkxMQkGcahQn3XrkS8OPeizwUGhRcahvL5kaWmJk1Mzbt++Q1hYhNHaeFHjRcMGdfX99OuvZrFixXosLMoUr7NlJ130Oq6F/OPs7AiAqcoUCwvd+GFhaUFS0mUATExM+PLLGWza5EVOTk6J+Q90sSjPDqCFU1Oio2KJzdXcunknvd0MLzV6u3Vj3dqtAGzftpuOnR9vjMqLFXnxrqRiEpTeuFTSY23dug5Ur16V48fPFFsWBePy3G8MnhYp5Rwp5f7nXY4SwAaIz/tHq03SD9J5aGysiE9IBCA7O5u0tJtUrVoZG40VCbn789JqbKyoU8eea9eu8/eSH/E9s4dFf36HpaUFAA3q18G5bXNeadqItduX0LT5yyQlXqamdXUDzZrWNUjSJus1b928TeUqlfDevp+7d+9zKmQfPoHeLP5tJWmpNw3SegzoyY4tuwGw0tQkUZukP5aoTcYq35ILAGvrGmhzbXRat6hSRTe1X8velv3HtrB15ypat21JQQYMdsNzqzcaTU0StIa+sNYY6uS3yc7O5ubNWwZT4wD9+/cmOCiEjIwM/b5Ff37HyVO7+GT6+Nx8ivB7Ia0HNsVpFcewYf3YuHEH1horEhLy+y4JTUHfaWrqbfJ0quTqODk147Tvbk6e8WbShFn6GwUTExN8TnoRGePLoYPHSUu7ZfT6ZGVlMWHCp/j57SU62o+XXqrPsmXr0GgetOU8rULt/Sl8N/ezj9m374i+HRWb9xP2JdBdgHrvWsvpU96MfWsEGpsHtl/M+4Qpk9/FqWUz5n7+3SN1CtY/IZ9OUWhsrFCr1XTo0IoTPjsYNXIwjo6NH6tOj6Nlb2+LY7PGnD4TUEjbpEx5cjLvFVs2Y2CVL84AJCdeKRQfalrXICmxuFh0j9Oh+zketIfFv63QxyIpwdZOw/YDa3lt9KAitS0sytDTtTNbtuqWYjRqVI+hQ/rS0aU/Ts6uZGdnM3z4wELpHuZXlcqExo0bcuz4dt548zW02mQ0hdp3TRLyxbu0R8ShrKwsJk2czWlfbzZvXYba1JQVy9cDJTde1K5di4SERNzde6BNTObs2WBUKsObRJt88UlXj9x2Z2NtELe0CcnYaKxJTEzmx58WERlxmrhYf26m3WJ/7o3o+++/wc6d+3N/xJD5ymhc/0VEnaZRo/qsXrlRb2ttXZPEhAdtMDExudDYYW1dE23BOJu7HKmWvS0Hj21j+67VtGnrVOhcFPR5ScQknV9KZ1wqybEWYMjQvmze5PVYZSptckphex48lxsDIcSnQohwIcR+oGHuvrpCiN1CiLNCiGNCiEZCiIpCiBghdAtbhRCWQoh4IYRaCLFcCDE4d7+zEOKEECJICHFGCFFeCKESQnwnhPAVQgQLId55SHk6CyGOCCE2CCEuCiG+EUKMyM3rnBCibq7d/7F33mFVHN/jfpcLqCjYC01RsTfsFcUCVgQbdo2xa+wlJsZeYjSWaIw9ajSxKyodFBU7KE0QUBQLxUKzK2V+f9zrhcsFS4Ik389v3+fZB+7szDkzZ2dmd3ZmzlaSJOmUSt4pSZIqqsIrS5J0SaVrSQ7Zs7LlQXvBYQ7WrFlje+DAAQdJkgIyM5Vv3rN3jCqZWumEyCtcoKtQ0LBhPbZs+YOmzTrz8uUrZs/+BgCFroIiBgb4eJzlxwVr2bB9pVrex3UKGjSqQ2ZGBi3r2tGucXdGTRiKeSVTdRw9PV06dmmH+wlvlZxcCq2tLNcojxIe06hOBzpZ92bB3BVs2v4zxQyLasRz7NONY4dd88zvx/VkxalVqxpLls5h0qTv1WFffz2FZs26YNupH61bNWXw4D6fpOuT8pMH/fr15ODBE7naTksPuUYCICAgmOZNu2DT1pEZM8dTqJDyzUxmZiZtWvagVvVWNG5cH3PVmu38LI+uri5jxgylRYtuVK7chNDQm8yePfETbZdbkfLWVb9+bapWrUTAteBPkP15bQmgnY0jzZp3oYf9EMaP/4pataqp48yb/xPTZy4gKiqaiROy9ur8HT25IUkSko5EiRLFadXGngMHj2Nna/OPywTKWZaDB7YxfeYCnj/XnNDUKVICBIi3H50M/Uf8k7bUoFFdMjIyaFHHlraNujFq4jB1XzRhxAzuxTxkRP+JDB3ZH+scsywAPXrYcfFSAMmqWZoO7dvQqGE9Ll9yI8Dfiw4d2lClcsXPyvOSxas5edKb3o4jGDNmKNWrV/nstlSrVjUWL/2WyZOUe0l0dXUZNXowrVv2YPI335OUnMrMWRNyTZu3/M+7Xzg4dkWhq+C7OZNZtOhnrXQfKkde7bdEieLY97Cjeo2WVLJoTNGiRRg0sDfGxuXp07s7mzftzpe+9UP2s6zSnBs3Ipg6Y+wny8szDoJHCY+xqmNDB2tH5n3/I1t2rNa4R/398nxen9SmTfMCvC99mXvte/r2tefgoROflCeZ/KHABwaSJDUGBgANgd5AU9WprcAkIURjYCbwmxAiFQgG3u+ysQc8hRBp2eTpAweAKUKIBkAn4DUwEkgVQjRV6RgtSVLlD2StATAFqAcMBaoLIZoB24FJqji/An8IIeoDfwLrVeG/AJtUutSvGiRJsgOqoVweZAU0liSp7YfsM3369F39+/e/LoRooqNTFFNTY+JU06vviX0Yj7mZ8uFNoVBQvLgRSUnJPIyNx8ws66HO1NSY+LhHPIyN5+HDeK76K98CHjnqSkOrempZvt7nMDYpT0hgGJmZmVSxrMTjhCcaOhPiHmGsfgumwNCoGCnJqfTs05Wzpy6Snp5O4tNkrl0Jop5VbXW6dp3aEBYSwdMnSQDExz7CxNRYfd7EtAIJCY81dMXHPcJUFUepy5Dk5BTevUtT37RDgsKIufuAqpZZl7R23Rro6uoSEhRGbGwCZqaatsg+XQzK2Yr3cRQKBUZGhiQlpajztW//FkaPms7du/c18gbKJRcHD56gSZMGxOZm9xy6ssfJqetD1KtXC11dBYGBocr8mmW3nTHxOWwXF5cVJy89UZHRvHz5itq1a2iEp6Y+57zfFSwszPO9PA0aKOvEnTv3ADhyxIUWLRoTG5tVl9/r0qrvsQmfpatF88Y0bFifNasXYW/fmWrVKuPjfShf2hKgXu7w5EkizsfdKVOmtEZcM1Njzl+4Qq9e3T6qJ2f5zbLpyY3Yh/FkZmTi7OwOwLt3aaSnp1OmTKl/pEtXV5dDB7axb98xtez3SIWKIekbkPFcsw58CeKz9TMAFUzK8ShHHU+Ie4SxiXZf5NC3K+dOv++Lkgi4EkR9qzoA6v4n8WkSnq6n1UtZstPfqafGMiJJktiz9xBNmtrRpKkddeq2ZfGSNTg4dFFvVm7cqP4H7Rp2IxIzU2OePEnk5ElPGjSoo64/71H2VVlttniOfuiv/VsYM2qGuh+qr2pLd+/eJzY2npcvX9G8RSMgj/aTD/cL4wrlqFatChYWFQnw92LNmkUULWrAlcselC+vnF1WysteDiOSklKIfRiv0W+ZmlUgLj6Bjh3aEBPzgKdPk0hPT8fZ2Z0WLRtjZVWHqlUtCLlxhpU/L0BXV5fgUF9VHivkq/0Ajh5xpWnzRmp5cXEJmJhl1UETkwra9464BExz9LPJSap7lEp3cFAYMXfvY5ntHqW0xUf6u3zok5o2tSqw+9KXutdm1xMUeOOjefo3EEhf/Pg3+DdmDKyBY0KIV0KIZ8AJoDDQCjgkSVIQsAV435McAPqr/h+g+p2dGkC8EMIfQAjxTAiRDtgBw1TyrgClUT6k54W/ECJeCPEWiAa8VOGhgIXq/5bAe5cWe4A2qv9bA/uyhb/HTnUEAteBmh/JA4C/Kk5lPT09+js54OLipRHBxcWLoUP7AdCnT3d8z1xQh/d3ckBfXx8LC3MsLStz1T+QR4+e8PBhHNWrVwWUngBu3owC4MQJT8qWL4tFlYq0bNMEPX09OnZuh4/HGQ2dpzzO0meAPQBde3bikp8/AHEPE2hlrRzbFTEojFWT+ty5FaNOZ9+7i3oZEUDg9VCqVK1ExUqm6Onp4di7G55upzV0ebqdxmmQozK9Y2fOn7sMQOnSJdVrfCtZmFGlaiXuxahXXdG7b3eOHXYF4Nq1YKpaWlCpkhl6enr07WuPq6u3hh5XN28GD1EuK+jVqxtnz14ElB45jh7ZyYL5K7l8+Zo6vkKhUE9/6urq0qVrB8LCoggICMbSsjIWFubo6enRr589Li6aulxcvBkypK8yn727cebMRT4FJycHDh48oSpTCFWqZpWpT98euLlqrqZzcz3FwMHKMjn26srZs5eU9qpkpp76Nzc3oVr1Kty7/5DSZUpRvLhyPXjhwoWwad+aU6fO53t54uIeUbNmNfUDbMeO1kRE3FbZzkKty6lfz1x1DVXr6s4ZVX3Pi63b9lC5ShOqWjbnyZOnxMQ8pGu3QfnSlgwMilCsmPINoIFBEWw7tcPT0xdLy8q0a9dKWQYnB9LTM4iMjFbrOZmHnpMuXjjloicv/AOCAEEvx67o6ekxdGg/3r1L4+nTpH+ka9vW1dyMuM26X7Zq6OtsZ4OiSAkyniVQEJ/zCQkMw6JKRcwqmqKnp4t9ry74uJ/ViOPjcYY+A3oC0LWnLZf8lGuPYx8m0FK196mIQREaNqlH9K27FDEogkHRwupw6/YtCQuL1JBpZGRIW+sWnDjhqQ477Xue3r16qD2PlSxZgooVTTl+3EM9WLh2PSRPuxoYFCEyMpqqlhbUrGlJx05tqV6jqnabdfPJ1g9ltdnixQ05cuR3Fuboh+LiEqhZS9mWrl0LwdLSgvi4R3zJ+8Xly9eoUL4crdv0oE7dtjx4EEdCwmOat+jCo0dPVPK8s/Rka6cuLt5a9vH3D+L+gziaN2+o3qvQvn0bIiJu4+5+moqVGlGnljU1q7dCCEHPHkPV/Xh+2g+gQ8c23MrWVgOvhVKligUVVf1srz7d8XDT9Azm4XaaAQN7AdDTsQt+Kp2a9yhzqlS1ICbbPco/IEijb/1SfVJYWGQB3pfy/177nn79enLo0MlPypNMPlLQu52BqcCibL/XAPNRPtznFr8YcA8oBdwHFKrwXUBfoD5wPpd0R4DOn5gnG8Al2+8zQJOc54CngJ7qfz3gier/REBX9b8R8EL1/2pgbB46X3wgT92EEFG3b98VP8xbIXT1TMSSpWuEY6/hQlfPRBQtVlkcOnxS3Lp1R1y9el1Uq95C7Yngh3krxO3bd0VE5G3RvcdgdXjjJrYiICBIhISECefj7qJM2VpqjxPHDrqIB/dixZs3b0RC/GOxaukGUbm0lfhl1RYxavAUUbm0lahh0ky4OnuJu9H3RNC1UNG2UXdRubSVqFOxpXB19hKRN2+LqIhosXzBGrU3olpmLURSYrKob9FGHVbOqIYY2Ge0uH3rrrh7555YvniNKGdUQ/y84lcxtP84Uc6ohjAvW08cP+Yu7kTHiOsBwaJp/Y6inFENMWLIJHEzPErcCLkpgoNuiCFO4zS8EcXcvS9aNe4iyhnVEAZFKolejsNFVFS0iI6OEQsWrBQGRSqJ5cvXib59RwqDIpVEyRLVxZEjLuL27bvC3z9Q1K7VRhgUqSQWLlwlXrx4KYKDw9RHpYqNRJnSNcX16yEiNCRchIVFio2//i6KqDwT9ew5TK1r/vyfRKFC5mLZsrWid++vRaFC5sLIyFIcPqzUdfVqoKhZs7Xas0NMzH2RmJgsnj9/IR48iNPwHHHnzj1Rr56NKFTIXBgaVBZ9eo0Qt6LuiDvRMWLRglXC0KCyWLH8F+HUd5QwNKgsypSsIY4ecRXRt++KAP8gUa92W2FoUFmMHjlNhIdFiuDgMBEYGCoGOI0RhgaVRYtmXUVQ0A0RGnpThIVFiKWL13yx8kyc+J24eTNKhISECxcXb2FsXE/oFzITPXsOVeuaN/8noV/ITCxdtlb07j1C6BcyE4ZGVcXhwyfVumrUbKX2PHQ3h66cHo1GjZom3rx5K/KrLVWr3kJdJ26ERahl9rAfIp49fy7evn0r4uMfiZMuXmLtuq3CoddwodAzEQY59FhWb6H2apNTz/vwffuPibi4BPHu3Tvx4EGcGDV6utJzTq/hIjX1mXj79q2IjY0XnWz7iSVL1/xtXW3bOQghhAgOCROBQTdEYNAN0cN+iFDomYhbt+6IzPQ0kZn2RmSmvRHpr1I/6l1oyoTRolXL5qJ2rVrCunVLse/33z7ZK5FFqfriK6cJ4s6tGBFz575YtXS9sChVX/yycrMYNWiSsChVX1Q3biJcnT3VfZF1w67ColR9Udu8uXB19lT1RbfF8vmrhUWp+sLb3VekvUsTmZmZ4t27NOF+0keMn/CtGD/hW7VdRnw9Vew/4KzlcWjAoHEiMOiGCA4JEwHXgkWr1j1y9UyUm10tq7cQIcHh4u6de+LNm7ciMTFZLFywShQtYiF+XP6L6Nd3lChaxEKUKlFdHD3iquqHgkSdWtaiaBELsWjhz1r9kEXFxqJoEQsxedL3IuLmLREaclNcvRoooqNj8q2O53W/6GE/RERGRYvb0XfFvHkrxN2798XqNZtEr95fCT19U1HMsIo4fPikuKVqp9VrtFR7GJo3b4W4HX1XREbeFj3sh6jDlyxZIyIibokbN26KvXsPi6LFKqvPvfc69OrVaxEVdUdER8d8Efu5uvoIy0pNNbwH9e8zSty+dUfcuXNPLF20WpQ2rCZWrdggBjuNFaUNqwmTMnWE81E3ER0dI64FBItG9TqI0obVxPDBE8XN8CgRGnJTBAfeEIP6jdGQ+76viIyK/uJ9UkHdl77Evfa9N6I7d+4JqwYd1L8L+nn1Y4dvub7iSx//Rrkk1UNqgSFJUiOUD/XNUX5g7TrKGYLewFohxCFJuWitvhAiWJXmEPAGeC6EmKAK2wW4oJxxiAD6CyH8JUkyRLmU6GugG9BPCJEmSVJ1IFYIoekyRynLBpgphOih+n1G9Tsg+zlJkk4Ah4QQeyRJ+gpwEEL0UoUfFELslSRpPLBKCFFMtZRoCdBRCPFCkiRTIE0I8ViSpBdCiGIfspWevmmBXBxzo3IFoQaAl1948+J7XqTl7U0hP8n4RG8n+YG+omC+R/guI71A9IByXW5B8Kleaf4pBdubFgyv4/wKRE/1Gr0KRA/Ag+dPC0RPYd28vZnlN2/T3308Uj6Q25ryL4G+Qq9A9AAU1i0YXalvtB4/vhiKT/Aglj96Cm7hyctXMf+pL4qdKd/vi3f5No8OFXiZC/zLx0KI65IkHQCCUM4EvL/rDAY2SZL0A8q38ftR7i8A5fKhQyjf3ueU906SpP7ABkmSiqAcFHRCuTfAAriuGmg8ARz/YfYnA79LkjRLJe/97sIpwF+SJE1BOVPxPm9ekiTVAi6pOtMXwBDgyy/WlZGRkZGRkZGR+SJk/kt7AL40BT5jIPPpyDMGfx95xuDvI88Y/H3+F3tTecbg7yPPGPx95BmDf4Y8Y/DlOV3e6Yt3+R0eHfzfnzGQkZGRkZGRkZGR+b/Mv+U16Evz/9XAQJKkemh6DQJ4K4TQdmotIyMjIyMjIyMj8/8R/18NDIQQoSi/JyAjIyMjIyMjIyPzt/i3vkz8pfn/amAgIyMjIyMjIyMj80+RlxLJ/M8SfnxmgelaMcitQPQsiz9TIHosS5gWiB6AO8/iC0TP4AoFt7JuT9ylAtFjYli6QPQkvn5eIHoA3hTQZtOC2hQcFXmsQPQAODWaUiB6ziZHFIgegBalqxeInrDnDz4eKR9Iyyw4JwiZBeSEpSCdExTTL1wgetIyMwpEj0zBIQ8MZGRkZGRkZGRkZD6D/9WlRAXnZ0pGRkZGRkZGRkZG5j+LPGMgIyMjIyMjIyMj8xnIMwYyMjIyMjIyMjIyMv+zyDMGMjIyMjIyMjIyMp/B/6pXInnGQEZGRkZGRkZGRkZGHhj8R+kCRN4MP8+sWRO1Turr6/Pnn5u4GX6eC+dPUqmSmfrc7NnfcDP8PDdunMPWtp06/FbUZQKv+xDg78XlS5ouQxXG1dFvZI9+w+7oVmoIwIXQ2/T8biM95mxgh+t5rTzEJ6YycuVunBZupe/8zfiF3AIgLT2DeTuO02feZvrN34J/RMwHC2rZrj7fnF7F5LOraTPeXut8k8EdGe+5gnFuy/n68HzKVlO6B63Spi5jXJYy3nMFY1yWUrlVbQ15BWG7FT/+gOuFgzif+ZMNu1ZiaFQMgDbtW+B28RAeV44watIw7TK1aMgRnz8IjbuIXY8OGue27v+FK7dOsWnvmlztZWdrQ2jIGcLD/Jg5c0Ku5du75zfCw/zwO3dCXb5SpUrg6XmAxKcRrFu7RCONnp4ev21cwY3Qs4QE+9K4i6a70rrtrFh+6hd+PLOBbuMdtfM0sgdLvdeyyH01M/9cQGnTMupz26MPsNBtFQvdVjFp27daMvPrOhUqVIiLF1y4FuBNUNBp5s+foY5vY9Ma19MHOB/owY27Fzkb4ML4KV/nolOPX7ev5Ky/C85ef2JmbgKAY99uuJ05qD7uPgmidt0aAPTs3RVPvyN4nDvM7oObKF26JJ1s23I96BTBob5MnzEu17Lt/mMDwaG++J49RsWKyjrdvkMb/C6c4MpVd/wunKBdu5bqNBMnjuBJ4k2eJt3kTow/cQkhTJ40SkNujRpVOX/uBC+f32H6tLFaej+Fb2d/Q0T4ecJunMMuWxu4evMUEXH+RMb5czHUK1fbbdi+El//kxzz2oupyna6urr8vHEJ7n6H8b50jPFTs+zuF+iGu99hXM8c4Pipvz47rz8sX0Pb7gNwHKJt48+lYbtG/Oq7id/ObaH3hL5a53uOcmD9qY2s9VzPon1LKWtaVn1u3h8L2Ru6j7k75+cqu2Mna65c9yQgyIcp08dondfX12fHrnUEBPngffow5hU1XSCbmhlzPz6IbyaP1AjX0dHhzPnj7Du0NVe9TW2asPPMdnb77WTABCet8/Wa12WT26943nXDulsbjXOjvx/Jdp+t7Di9jYmLxmulbd+xDX7+rly87sE3U0dpndfX12Pz76u5eN0DV5/9mFU0UZ+rVac6J73+4sylE5y+4EyhQvoAHHHZhZ+/K95+R/H2O0qZMqW05HboZM3lax5cDfJm8rTcbKnH9p3ruBrkjefpQ2pbmlc05cGjEHzPH8f3/HF+XrtIK+2XuE5GxQ3ZtWcDl695cDnAgxbNG9PZzoawG+eICD/P7Dz6vr/+3ERE+Hku5uj7cmufZmYm+HgdIjTkDMFBp5n0TZb+v2uv7GWKiQtk4qSsdjtm/DD8Lrtw/oorYycMV9muLQHXvQkMPs206dp9j76+Pjt3rycw+DSnfI+o+7xGjevjd/EkfhdPcv6SCz3s7dRpihc35I+9v+J/3Yur1zxp2qyhltx/m0zpyx//BvLA4L+HAtgIdK3foD0D+jtSq1Y1jQhfjxhISnIqtWq34Zf121i+fC4AtWpVo7+TAw2sOtCjx2A2rF+Ojk7WJe5k248mTe1o0bKbOqxdu1bolDLjXaAr7wJdSY8LJyMzk+V73flt2iCOLZ2Ax5UwomOfaORh20k/Ojetw8GFY/hpbB+W71E+MB85e135d8k4Ns8cwuoD3mRm5u69WdKR6LbkK/4cvpKNnWZTt2dL9YP/e0KPX2RT5zls7vY9Fza70PmHwQC8Sn7Ovq9/ZlPnOThP30yvteM15BWE7XxOnaNn24E42gwmJvo+Y6Z8hY6ODvN+ms2YgVOwb9Of7r07U7V6ZY08xMUm8N3kxbge1X7A+n3jXr6duCBXe+no6PDLL0vp6TCMBlYd6O/kQM2amuUb8dUAUlJSqF3HmvUbtrNs6fcAvHklImgbAAAgAElEQVTzlkWLfmbOnKVacufMmcTjJ4nUrdeOBlYdiLwSnu0a6TBk8SjWfrWMH2yn0bxnG0wszTTS3w+/y2L7b1nQdQYB7pfo991Q9bl3b96xsNssFnabxYbRP2nJzK/r9PbtW2ztnGjcxJYmTezobGdD82aNkCSJ33esY/LYOWRmZHB4/3G2rN9Fz95dqVajiobO/kN6k5ryjHZNe7Bj0x7mLJgKgPNhN7rZONHNxolp4+fy8H4c4TciUSgULFj+LQMcRtKlbV8iwqIYN344a9YuprfjVzRpZEe/fj2pWdNSQ8/wr5xISUmlQb32bNywgyVL5wCQmJhEv76jaN6sK2NHz2TbDuXgsFSpEnwzeSS1arSmTKla+HifJSM9A+fj7hpyk5JSmDptHmvWbtG6xp9CrVrVcHJyoL5VB7pns62Ojg4lS5agb9dh1K3UkpSkFCxz2M5pSC9SU57Rvqk9OzbtVduum4Mt+vr6dLXui32HgQwa3lc9aAAY5DCK7jb9ceg46LPz69jNls1rtOvz56Kjo8OYpeNYMnwhkztOpE3PtphVM9eIcyfsDjO7T2da58lcdL3AsO9HqM85bznKumm5D+R1dHRYuXohTr1H0bJpV/r07UGNGpr1YciwvqSkPKOJVSc2bdzJwsWzNM4vXzGXU97ntGSPmzCcqMjoPPVOWjqR74f9wMgOo2nv0J6K1SpqxHkc+4SV01dz2tlXI7x249rUaVKHMXbjGN1pLDUaVKdBi/oaspf//AOD+46lXXN7HPt2o3qNqhoyBg7tQ2rKM1o16sLW33bzw0LlQF2hUPDr1p/4dvoibFr2pE+P4aSlZX2v4JvRs7G17o2tdW+ePk3SKtNPqxfQv89oWjftRu++PbT0Dh7Wj5SUVJpZ2bJ54y4WLMqyZczd+7Rv40D7Ng7MnLZAS/aXuE4/rvyBUz7naNG4C9Yt7YmMimb9L8voYT+Eeg3a0z+Pvi85OZWatduwbv02fszW9+XWPtPT05k1exH16tvQuo0948d/Ra1a1f6xvQCW/vi9Rplq1qrG0OFO2LXvS7tWPbHr3B7LalVYvWYhfXt/TbMmnenTz54aOfq8YcOVeho26MBvG3eyaInyJdHN8ChsrB2xbmVPH8cRrFu/FIVCAcCKlfPx8T5H00Z2tG7Rg6jI28gUDP8nBgaSJC2UJOmzv8IlSdJiSZI65VMeLCRJ+vy71+fTDLgN3ElLS+PAwePY23fWiGBvb8eePYcAOHLElQ7t26jCO3Pg4HHevXtHTMwDoqNjaNb0w6PssWOHkfEwHIRqf33aW27cicW8XEnMypVET1dBl+Z1OBMUqZlQghev3wLw4vUbypYwBOBO3BOa11Y+CJc2KoqhQSHCYuJy1W1qVZWkmEckP3hCRloGN05epoZtY404b1+8Vv+vZ1BI/YGYhLB7PH+cAsDjqIfoFtLDvEl1tbyCsJ2PzzkyMpQfdwm+doPyJuWo36gO9+8+5OG9ONLS0nE75kWHLm010sU9iCcq/DaZmdo+DS77+fPyxatc9TVtakV0dAx3794nLS2Ng4dOYJ/tDYu6fHsPA3D0qCvt27cG4NWr11y86M+bt2+15A4f3p+VK38FQAjBi+Ssj3RVsbLk8b0Enjx4TEZaOldOXsDKrqlG+ohLYbx7o/zY1p3AW5Ss8OGPiWWXmZ/X6eVLpd309HTR09NDCEHp0iV5+/YtxYsbEnP3Pq7HvbHr1p6Txzyw7dpeQ6dtVxuO7D8BgNsJb1q31f7QW88+XTlxVPlALkkSkgQGBkUAKGZYFP1C+tyJvkdMzAPS0tI4fPgk3XvYasjo3t2WP/ceAeDYMXdsbFoBEBIcTkL8YwDCw6MoVKgQ+vr6WFSuyO1bd9UPSgmPnvD23Tvu34/VkPvkSSIB14JJS0vTyvegQb25dMGFAH8vftv4k8agV102+84czMW2DRrVJT09ndgH8aSlpatsZ5PDdu3VtnM/4U2rts0AZX0yMCiCQqGgcOFCpL1L58XzF1q6/w5NrOpR3MjwH8upZlWN+Jh4Ht1/RHpaOudPnqOZnea1v3EplHdvlG0nKjCS0sZZdTz0Qgivs/VT2WncpD5379zjnqo+HD3iStceHTXidOveif1/HQXguLMHbW2yZoq69ehETMwDIm7e0khjYlIB28427Nl9MFe9NaxqEBcTR/z9BNLT0jlz4gyt7VpqxHn08BF3I+6SKTT7ISEE+oX00dXXRU9fD4WeLslPk9XnGzauR8yd+9y/95C0tDSOH3GnczfNmc8u3TpwcJ8zAC7HvbBu1wKAdh1ac/NGFOE3lPeT5OTUXPvB3GiUw5bHjrjStbvm7b1r947s36f8UN4JZw+sbVrmJkqLL3GdDA2L0apVU/bsVvZjaWlp1KheVbMPP3icnjn6vp559H15tc+EhMcEBt0A4MWLl0RE3MLUpMI/tlfX7p24F/OAyIisB/LqNapyzT+Y16/fkJGRwcULVxk3bhh37mT1eUcPu9A9h55u3Tvx159K2zkfc6edSs97OQCFCxdCqD40Z2hYjNatm/KHqn6npaWRmlpwH4/8VDKRvvjxb/B/YmDwdxFCzBdC+OSTOAugIAYGpoD605KxsfGYmlTQiGBiWoEHD5UP2xkZGaSmPqN06ZKYmlTg4cOsh/DY2HhMTJVphRC4u+3jymV3Ro0crI5TvVoVdIzKol+/M/p1OyEVK8XjlOdUKFVcHadcSSMeJWs2yvEO7XC9FIrtjLVMXLePOYO7KOWZl+dMYCTpGZk8fJLMzZh4HiU9y7WgRhVK8Sw+Uf37WXwSRhVKasVrOsyWyefWYPvdQNwX7NY6X7tbMxLC7lGsTHENeV/adtnpPdAev1MXKVehLAmxj9Thj+IfU964bK5pPhcTk6y851m+bOXIyMjg2bPnlC6tbdP3FC9uBMDCBbO4fMmNv/7chFGZrGtfonwpkuKeqn8nxydSsrz2FP97rJ06EHomUP1br5A+80/8xNxjy2moGlDklJlf10lHR4cAfy/iYkPwOXWOq/6BPH2ahJ6eHs1aNSY+9hHdetpibFqB+LhHVDAup6GzgnF54uIeqXU+f/aCkqVKaMSxd+zM8SPKgUF6ejo/zFyG5/kj+IedolqNqgQF3uBhbNYXqmNjEzDRukbl1XEyMjJIzeUaOTp2JSQ4jHfv3nEnOobqNapSsaIpCoWCPn16kJiYzKdSs6YlTv16Yt3OkSZN7cjIyGDQoN5a8XLWr4cq21YwLkd6egZ/HN7MiVP7sKhSkQrG5TXSljcuR3xcgpbt3E/48OrVa66E+3Ah2JNtG3eTmqLsD4RALXPgsD6fXJ78plSF0jzNVh8T4xMpXT7vwW2n/rZc9732SbKNjSsQm60+xMUmYJzDdsYm5Yl9mGW7Z6kvKFW6JAYGRZgybQwrf9ygJXf5T3NZOG9lng/VZSqU5nFc1izvk/inlK5QJte4Obl5/SZBl4I5GLCPg9f2EXD2GvdvZ33tuIJxeWJjE9S/4+MScm9LsdnK9Ow5pUqVoKplJQSCfUe24nX2MBMmay7pW7txGd5+R5k2S3t5mLFxeeIeZumNi0vA2KS8VpzYh1ltS6lX2bYqVjLjtJ8zJ9z20qJlkxzp8v86VbIw5+nTJH7d/BNnzh/nl1+XUblyRe029ol9X17tU0NnJTOsGtTlytXAf2QvA4MiTJ42mlUrftWIfzP8Fi1bN6FkqRIUKVKYTnbtqFTZXC0DlH2elh6TCpp6Up9TStXnNW7SgMv+7ly84sa0KfPIyMjAQmW73zavxO/CCTb8ulz9Akbmy/OfHRhIkjRXkqRISZJ8gBqqsKqSJHlIknRNkiQ/SZJqSpJUXJKkGEmSdFRxDCRJeiBJkp4kSbskSeqrCm8qSdJFSZKCJUm6KkmSoSRJCkmSVkmS5C9JUogkSR9amLsCsJYkKUiSpGkq/VbZ8ntBkqT6qtmNPZIknZYk6ZYkSaOzxZmVTZf2IkdgzZo1tgcOHHCQJCkgM/MlgHoUnU2OVjoh8gpXpm1n40iz5l3oYT+E8eO/ok0b5Rsxha4CdPV5F+JJWkwgejWsye3r8DlFu1+5Qc/WDfBePY2NUwcyd5szmZkCR+uGlC9pxKDF21i1z5MGluYoFJ9ezXKWFcD/D2/Wt52Oz4r9tJ2kuca9bDVTOs0ZwMnvdnySvPy03XvGTh1BRkYGJw975Ck/P/hQHrPiaKfLzabv0dVVYG5mwsVL/rRo2Y0rV67j9H3WvohP0fmeFo7WWNSvisfW4+qwWa3Gsbjnt2ydvI6B80dQtmL5TyzH51+nzMxMmjS1w6JyE5o2aUidOsp9AEOGTKDvAAdsu9rw8sVLMtLT89CpXabscawa1+P16zdEqd6g6erqMuRr5RKjpnU6EhEeRU+HLn+zbFlxatWqxuKl3zJ5knIJQUrKM6ZOmcfuPb/ifeoQ5cqV0RgcfYwO7dvQqGE9Ll9yI8Dfiw4d2lClckWteHnlS5IkTnmexb7DAEb0n0jrdi0oV77MJ6Vt0KguGRkZtKhjS9tG3Rg1cRjmlZTLBft2G66WOXRkfyTdwp9cpvzkc+p4u142VK1vifOWo58oWzvsU+vDnLmT2fTrTvVM2HvsurTnyZNEgoPCPqA3V8WflGcTCxMqWZozoNlg+jcdRMNWDajXvO6H8/sJ+oUQKBS6NGvRiImjZ+PQZQhde3SiTVvlbMLE0bPp0NoRx65DaN6yMU4DHT9J5kfjIHiU8BirOjZ0sHZk3vc/smXHaooZFs2WTtsO//Q66eoqaGBVh53b/8KmjQOvXr7G0bHr39Tz8fIXLWrAwQPbmD5zAc+fv/hH9vr2+8ls3rhLq0y3oqJZv3YbR5x3cvDoDsJCI8jM0B6c5qxqH7LvtYBgWjTtSvt2vZg+YxyFCumjq6tLA6s67Nj+J9ate/Ly1Wum5bJf699GFMDxb/CfHBhIktQYGAA0BHoD79cubAUmCSEaAzOB34QQqUAw8H6nnD3gKYRIyyZPHzgATBFCNAA6Aa+BkUCqEKKpSsdoSZI0F4RnMQfwE0JYCSHWAtuBr1TyqwOFhBAhqrj1ge5AS2C+JEkmkiTZAdVQLhWyAhpLktQ2hw6mT5++q3///teFEE10dIpiampMXPwjjTixD+MxN1Ou01UoFBQvbkRSUjIPY+MxM8tav2tqaky86g1ovErGkyeJOB93p2lTK7WszETl2yDxIhGEoHyZ0iQkparlPE5+RrkSmlP2x/yC6NxMueG3gaU5b9PSSX7xCl2FDrMGdubgorH8MnkAz1+9oWK53N8wP0tIwijblLyRcSmeP0rJNS7AjROXqGmX9abHqEIpBmydxrHpm0m+/1hL3pe2HYBD/+7Y2LVh1vh5gHKGoIJp1tuS8sbleJyguT/j7xIbm5X3PMsXm6Auh0KhwMjIkKSkvG2amJjMy5evOH7cA4AjR12oVDdr/XhyQiKlTLIeAksalyblsfbb6tqt69Hjmz6sH7WC9HdZa4bfx33y4DERl8OoWKeylsz8uk7vSU19xtlzF7GzswHg8pVrzJ48nxshN7ly8Rp379zH2KQ8j3Jcl/i4R5io3nQpFAoMjYqRkpzVDux7dVEvIwKoXU858Lgf8xAAF2cvzM1NMDM1zpa/Cur6oy5bbII6jkKhoHi2a2RiWoG/9m9hzKgZ3L17X53G3e0U7dv1YvXPm4iJeUB4WBSfiiRJ7Nl7iCZN7WjS1I46dduyeMkaHBy6EODvRYC/F40b1deqX2Yq28bHPVLPnCQ+TSIm+h6FChfS0JEQ9whj1ZvP7LZz6NuVc6cvkp6eTuLTJAKuBFHfqg6Aul0kPk3C0/U0kp6mzIIiMf4pZbLVx9LGpUl6nKQVr36bBvT9xokfRy7VqOMfIi4uAdNs9cHEtAIJCY8148QmYGqWZTuj4sVITkqhcZMGLFwym6Abvoyb8BXTZoxj1JghNG/RiK7dOhJ0w5ftu9Zh3bYFm7f9rCHzSfxTyplkzVSWNS5D4qNEPoU2nVsRHhjBm1dvePPqDVd9A6jVsJb6fHxcAqbZ3lQbm1TgUbxmmeLjEtRvs9/3Q8nJqcTHJXDpgj9JSSm8fv2G097nqNdAeR95v4zu5YtXHD3sSqPG9TVkxsUlYGKWpdfEpII6TfY4pmZZbcvIyJDkpBTevUsjWdXGgoPCiLl7H0vLyprp8vk6xcUmEBebwLWAYACOH/fAuEI57Tb2iX1fXu0TlC8pDh3Yxr59x3B2dv/H9mrUpAELFs/ieuhpxo4fztSZ4xg5ZggAf+45TIe2vbDvOpjk5FSiIqPVMkDZ5yXkKJPSdtn0FDdUX4/3REVG8/LVa2rXrkFsbDyx2W3n7E6DBnWQKRj+kwMDwBo4JoR4JYR4BpwACgOtgEOSJAUBW4D3tfEA0F/1/wDV7+zUAOKFEP4AQohnQoh0wA4YppJ3BSiN8uH9UzgE9JAkSQ/4GtiV7dxxIcRrIcRTwBflYMBOdQQC14GaeejyV4VX1tPTo7+TAy4umptUXVy8GDq0HwB9+nTH98wFdXh/JwflumQLcywtK3PVPxADgyIUK6Z8O2JgUATbTu0IC1Ou8TxxwhOdEsrOQypsiKSjQ52KZbn/KImHT5JJS8/A40oY7ayqa+TBuJQRV8LvAsp9Be/S0illaMDrt2m8eqtcb34pLBqFQoeqprkvpYkLvkPpyhUoYV4WhZ6CuvYtiPTWnKIvZZH1kF2tgxVJMcqp0cJGBgzaOROflQd4EBClJa8gbGdnZ8Oob4YyYegM3qj2W4QGhlOpijmmFU3Q09OlWy87fD39ci3/5xIQEIylpQUWFubo6enh1K8nLi7eOcrnzdAhSq8qvXt354yqfB/C1dVH7QGnffs2xN16qD53N/g25S2MKWNWDoWeLs3tWxPk7a+RvmKdygxbPpb1o1bwPDFr2ZiBUVF09ZWfSilW0pBqjWsSf+uhhsz8uk5lypRSL4sqXLgwHTtYE6namFm2bGmCA8OoUrUSU78dz/69R7Hv1QVv9zMaOn08ztBnQE8AuvW05aLfVfU5SZLo7mCnMTBIiH9MtepV1FPi1jYt8L8aRFVLCypVMkNPT4++fe1xc9Vczejm5sPgIcqlM716deXs2UuA0gvHkSO/s3D+Si5f1mwHZcsqB7yDBvemWDEDdu/K2cXlzWnf8/Tu1UMto2TJElSsaMrx4x7qwcK16yGcdPHCKRfb3oq8Q2XLSphVNMWouCENmzbA201zw2p223Xtacslle1iHybQ0lq536CIQREaNqlH9K27FDEoQtFiBupw6/YtEenvPrlM+cmt4FsYVzahnHl5dPV0aWPfFn/vqxpxKtepwvgfJ7J85BJSE1PzkKTN9WuhVKlqQUVVfejdpzserqc04ri7nWKAammXg2MX/M5eBqB750FY1W2PVd32bP5tF2tXb2b71r0sWbiaujWtsarbnlFfTcXv3GXGjdbcghcZHImphSkVVGWy6WnDRe/Ln5Tnx3FPaNC8PjoKHRS6Cuq3qMf921mD1KDrN6hctRLmlUzR09PDoU9XPN0164Onu6/6jX8PBzvOn7sCwJlTF6hdpwZFihRGoVDQonVToiJvo1AoKKUafOrq6mLbuR0R4ZqD38BroVSpkmXLXn264+GmaUsPt9MMGNgLgJ6OXfBTta3SpUuq99VUsjCnSlULYmKylkd9iev0+PFTYmPjsaymHIC0a9eSy5evYWlZOasPd3LgZI6+72QefV9e7RNg29bV3Iy4zbpfsjxU/RN72XcZRKN6HWhUrwNbNu1m3c+b2bF1L4DaW5SpmTE9etqxbu0WqlbN6vN69+2BWw49bm6nGDRYaTvHXl05p9JTqZKZerOxubkJ1apV5t79h9q2s2mlsdfhv0JmARz/Bv/lD5zlnEXRAVKEEFa5xD0B/ChJUimgMXA6x3kpF3nvwycJITw/O3NCvJIkyRtwAJyA7IsWc+oSKl0/CiE+5jIkHfgG8AwNOcOu3QcID49iwYKZXLsWjIuLN7/v3M+uXeu5GX6e5OQUBg9Ruq0MD4/i0OGThAT7kp6RweQpc8nMzKR8+bIcPqRcaqPQVbB/vzNeXmcA2LlrP+sXjEXfqjuITNJuXUJXocN3Q7oyfs2fyuVBbaywNC3HxmO+1LEwwaZhDWb0t2Px7pPs9bqCJMHikQ5IkkTS85eMX/0nOjoS5UoYsmyUtnvL92RmZOI2fxdD//gWSaFD4MGzPLkVS/vpfYgLuUukz3WaDbejSpu6ZKZl8PrZS45N3wxAs+F2lLIoT7tJvWg3Sdmx7Rm6Qi3PXkz94rb7Zd1SihYxYMch5TrM4Gs3WDRrBUvnrGL7gfXoKHQ4+tdJbkfeYdK3Y7gRdBNfTz/qWtViw66VGBU3or2dNZNmj8G+7QBlGU5spYplJQyKFsE36CQ/TFvGBV/lDSgjI4OpU+fhcnIvCoWCXbsPcPNmFPPnz+D6tRBcXL3ZuWs/O39fR3iYH0lJKQwdluUOLzLyIkaGhujr62Fv35nuPQYTEXGLuT8s5/fff+HnVQt5+jSRA3Oz9nFkZmSyd/52pv/xAzoKHc4fPE3crYc4TutPTGg0QT4BOH03lEIGhZnwm9LzSGLsUzaM/gljSzOGLx+jXo7itukYcbeVg473MseK2flynYyNy/P7jnUoFDpIOjocPnwSNzflA/mM6eNxsO+Mrp4elatUZNmqHzj4lzO3IqOZPmcCIUHh+Hic4cDeY6zdtJyz/i6kpKTyzajZajs0b9WY+LhHPLiXteH3ccIT1q3azCGXnaSlKTfnfj1qKr6+53E+8QcKhQ57/jjEzZu3+GHeNK5fD8XN1Yfduw6wfcdagkN9SU5O5athkwAYO244VapW4tvvJvHtd8owB/thPHmSyMpV86lfvzaWlpX5ZuIcbt9WDsrHjFZ6gNq6bQ/ly5flyiV3jIyKkZmZyeRJo6nXwIabN28xf+FK3N32oaMjkZaWzuTJc7U2L4eHR3H48ElCc9i2ZKniiEyBz2VnJEniysUA9v1xhGlzJhAaFIaPx1mV7Zbh63+S1JRnTFLZbs+O/azasBjPC0eRJDj813Eiwm9hXsmULX+sVbUrXU4ccaN+le559hW5MWvBCvwDQ0hJeUZHxyFMGDmUPjk2cn4KmRmZbJu3mQV7FqGj0OHUAR8eRN1n4PTB3A69hb/3VYbPHUFhg8LM2qT0IPUk7gk/jlR6RFp2eAWmVc0oXLQw267sZOOs9QSdUz6wZWRkMHvmIg47/45CR8Gfew4TEXGb7+ZOITAwFA+30+z94xCbt/1MQJAPyckpjBox7bPLkFuZNszbyIq9y9FR6OBxwIt7UfcYPmMYUSFRXPK+TI0G1Vm4bT7FihvSslMLhk8fxqhOYzjn6odVqwZs894CQuB/NoDLPlfUsjMyMvh+1jL2HdmGQqHD/r3HiIq4zazvvyE4MAwvd1/27TnChi0/cfG6BynJKYz7WjlwSU19xpaNu3E/fRAhBKe8z3HK6xxFDIqw7+g2dPV0Uego8Dt7iT92aW6szsjIYM6sxRw6tgMdhYK/9hwmMuI2c+ZOJuj6DTzcT/PnH4f4besqrgZ5k5KcymiVLVu2bsqcuVNIT88gMyODmVPna8wGfqnr9O3MJWzZvhp9fT1iYh4w/Osp+J65gJvrXyh0dNR938IFMwnI1vft3rWeCFXfNyhb35db+2zdqilDh/QlJDScAH/lIGPevBVcOnPlb9vrQ+zc+yulSpUgLS2d2TMWkZiYzMwZizjqvAuFQoe9ew4TcfMW3/8wlcDrobi7nWLP7oNs3b6awODTJCen8PVXUwBo0bIJ02aMJS0tHZGZyYxpC0hS7Z+aPWMR23esRU9fj5i7D5g4fjaTp47+UNZk8gnpQ+uP/y0kSWqE8g18c5SDl+soZwh6A2uFEIck5eK4+kKIYFWaQ8Ab4LkQYoIqbBfggnLgEAH0F0L4S5JkiHIp0ddAN6CfECJNtSQoVgjxMpc8NQbWCCHa5Qg7iXKJUX9V2ELAEWgBFEU5Q9ACqAssAToKIV5IkmQKpAkhNOf2sqGnb1ogF+e578qCUAPAikFuH4+UDyyLP1MgeixLmH48Uj5x51n8xyPlA4MraHvj+VLsibtUIHpMDD/sKSm/SHxdcJ4z3hTQG3Zzw0/btPpPiYo8ViB6AJwaTSkQPWeTIwpED0CjElU+HikfCHv+4OOR8oG0zE9brpUfZBbQc9Czt7l7nPsSlChc9OOR8oG0zIwC0QOQ+iL6P/Wp4cPGg794xekb/2eBl/k/OWMghLguSdIBIAi4B7xfizEY2CRJ0g+AHrAf5f4CUC4fOgTY5CLvnSRJ/YENkiQVQTko6IRyn4AFcF010HiC8qE+N0KAdEmSgoFdQoi1QohrkiQ9A3bmiHsVcAUqAkuEEHFAnCRJtYBLqg0/L4AhQJ4DAxkZGRkZGRkZGZmC4j85MAAQQiwDluVyStvthzL+YdB0+iqE+Crb//4o39zn5HvV8bH8pAEajo0lSTJBucQp55eqooQQWp8ZFEL8AvzyMV0yMjIyMjIyMjL/Xf57623yh//q5uP/PJIkDUO5YXmuEOLf2iMiIyMjIyMjIyMjky/8Z2cM/i0kSaoH7MkR/FYIobHwWgjxB/BHzvRCiIVfLncyMjIyMjIyMjL/Nv+rb4TlgUEOhBChKL8zICMjIyMjIyMjI6NF5n9qK3T+IS8lkpGRkZGRkZGRkZGRZwz+y5QoUqxA9PQd+FeB6AEIe/nw45HygWL6RQpETwm9gnEJB9CqTM0C0dMwo3CB6AH4S0dRIHpaFSsYV47eaeEFogfgbQG5K33w/GmB6CkoF6IAB68XjA8Ii2r2BaIH4OaLgulbk94UjEveCkVLFogegLcZaQWiR0cquFfMRvoFc296lf6mQPT8F8nkf3PKQJ4xkJGRkZGRkZGRkZGRBwYyMrwNQK4AACAASURBVDIyMjIyMjIyn4MogONjSJLURZKkSEmSbkuSNOcD8fpKkiQkSWryMZnywEBGRkZGRkZGRkbm/xCSJCmAjUBXoDYwUJKk2rnEMwQmo3Sx/1HkgYGMjIyMjIyMjIzMZ5ApffnjIzQDbgsh7ggh3gH7AYdc4i0BVgKftCFEHhjIyMjIyMjIyMjI/MeQJGmMJEkB2Y4x2U6bAg+y/X6oCsueviFgLoRw+VSdslciGRkZGRkZGRkZmc+gID5wJoTYCmzN43RucwrqrQmSJOkAa4GvPkenPGPwH6dDR2suBXhwNdCLydNGa53X19dj2861XA30wuPUQcwrKgeL5hVNuZ8QjK+fM75+zqxau0id5vt5UwkKO0NM7PVPykOjdo3Z7LuFree20XdCP63zjqMc+e3UJjZ4/sqyfcsoa1r2g/LadmjFqSvH8fU/ybgpX+dapg3bV+Lrf5JjXnsxNTcBQFdXl583LsHd7zDel44xfqpmWh0dHVx8D7D9rw0AdOzUlqvXvbgWfIqp08fmokefHbt/4VrwKbx9D6tt9x4zM2MeJATzzeSRAJiaGnPCbS+Xr3lw0d+dsROG51q+FjZN2X9uN4fO72XoxIFa562a12eXxxb87vnQvntbjXPn7/uw22sbu722sXLn0rxMCEBTmybsPvs7e8/vYuDE/lrn6zevxxb33/CJ8aBtd+ss/a0asM1zs/rwvO1K686t8tRT0aY+Q86sYqjfahpP0Ha/WHdIBwZ6/8gAj2X0OTKPktWU16u6YysGeCxTH9/c+4MytStqpbe1bUdIiC9hYeeYOXOC1nl9fX327NlIWNg5zp07TqVKZgCUKlUCT8/9PH16k7VrF6vjFytWlCtX3NXHw4dBDJs/UkNmg3YNWX16I2vPbqLn+N5aOruN6skqnw385LGOuX8tpoyqTpcxLcsyl9X86LaWVd7r6TS4c64269DJmsvXPLga5M3kaWO0zuvr67F95zquBnnjefqQVt0zNTMmJi6QiZOy6vi4iV9x/oorfpdd2Pr7GgoVKoSdnQ03bpzjZvh5Zs2amKvt/vxzEzfDz3Ph/Em17QBmz/6Gm+HnuXHjHLa27dThSYmRvH51j2ep0Vy+5KYlc8b0cQT4exHg70VQ4Cnevr5PyZIlcrVDXnw7+xsiws8TduMcdtl0b7mwnXVeG1jj/gurXNbQsF0jfvXdxG/nttB7Ql8tOT1HObD+1EbWeq5n0b6lGn3PvD8Wsjd0H3N3zv+svOXkh+VraNt9AI5Dxv2t9DYd23Duqgvnr7kzceoorfP6+nps2vEz56+5c9J7H2aq/g6gVp3qnPD8k9MXj+Nz4RiFCulTtJgBXueOqI/Q2+dZtFx7z+Hf1durX3cN+Q8SQ6lTV9NVsp2tDaEhZwgP88uzze7d8xvhYX74nTuRo80eIPFpBOvWLtFI4+V1kNCQM1y94sHVKx6ULlNKS267Dq05feUEZ/1dGJ/HvePX7Ss56++Cs9ef6jLp6uqyeuNSPP2OcOqSMxOmjtRK275jG877u3Hpugff5GGvLb+v4dJ1D9x89mNeUfM6uXjt4+ylk/heOE6hQvoUKVKYvQc243fVlbOXTjJ3wXQtmXZ2NtwIPUt4+Hlmzcyj/e79jfDw85z3O6lhRy/PgyQlRrJuXd73ibYdWuFz+Rinrx5n3OQRuZZp/fYVnL56nKOef2Bqbqy216pfF+N+7iBeF49o2PqrMQNx9zuEx/nDjBg76F+znQygnCEwz/bbDIjL9tsQqAuckSQpBmgBnPjYBmR5xuA/jI6ODitWz6ef4wjiYh/h5XsYD7fTREVGq+MMHtaPlJRnNGtoh2OfbsxfNJPRI6YBEHP3Pu2tHbXkerr7smPrn1y57vlJeRi/dDw/DP6BxPinrD25livel3lwK2v2KjrsDtO6T+Xtm7d0HdKNEd9/zcqJP+Upb/HK7xnaZywJcY847vMXPh5nuB15Rx3HaUgvUlOe0b6pPT16dWHOgqlMGjWbbg626Ovr09W6L4WLFMb74lFOHPEg9oGyHYwYO5jbUXcoZlgMHR0dVq1ZSK+ew4mLTeD0uaO4u50iMuK2Ws/Q4f1ITUmlcYOO9O7bnYVLZjNyeJYv9WU/zcXH+5z6d3p6Oj989yMhwWEUK1YUXz9n7l2NJubWPY3yzVg2hSkDZ/E4/gm/u23Gz+uiRpyE2EcsmfYTg8dpP8y/ffOO4XbaA8Dc7Dhl6SRmDfqWJ/FP2ez6Kxe9LnHv1n11nEexj/lp+ir6j9UczAVdDGZ0Z+VDjmEJQ/ae30XA2Wu56pF0JGyWDsd50ApexCfR32Uxd7yvkXwrq++JdL7Ejb2nAahs2wjr+UM4MXQlUc4XiXK+CEDpmmZ03z6dp+H3NeTr6Ojwyy9L6d59MA8fxnPhwklcXLyJiLiljvPVV/1JSUmlTp229Otnz9Kl3zF06ETevHnLokWrqV27BnXqVFfHf/HiJc2bd1X/vnjRlasel7KVSYcRS8ayfPACEhMSWXZiFdd8rhJ7K8sPfEzYHeb2mMG7N+/oNKQLg74bzvpvfib5cTILen9L+rt0ChkUZpXXeq55XyX5cbJGmX5avYC+DiOIi03A+8wRPNxO5dJuU2lmZUuvPt1ZsGgWo0ZMVZ9f+uP3nMpW9yoYl2f02KG0btaNN2/esn3XOgb0d+S77ybTtdtAHj6M5/IlN1xcvLh5M8t2X48YSEpyKrVqt8HJqSfLl89l8ODx1KpVjf5ODjSw6oCJSXk83PdTu441mZmZvHjxit59RrB27RJatOymVSdWr9nM6jWbAejR3ZYpk0eTnJyiXXnyoFatajg5OVBfpdvTfT+16mQNXOf1n8v/Y++8w6I4u4d9zy6gYK9Ue42994INRUSwJ/ZETWJeY+waTaxJNInRxN57Q0REqtJUwI40QURRVKpK1dhgme+PXRaWXSyJbvLLN/d1cenOnHnOnPO0efqTzBxkMhkbz25h6ZjvSU9J5xf3NVz2vURikbLnTvQd5tjN4tWLl/Qfa8v4hZ/y2/9+AeDE1uOUMi5F/zG2Wu/wLjgO7MfoYYNZuGL1Oz8rk8n48ddFfDJkCinJaXgFOHHaO5BbRdLCJ+OGkZ2dQ7e2tgweasuipbOYOmkOcrmcdVtX8c2X3xJz/SaVKlUgNzePly9fYdNjmPp578CjeHn4vje9rs6euDp7AtC4SQN2HVxP9PVYjbD/+OMHBtqNJjExhfMhHlp59tOJH5OVlUWTpt0ZMWIwP/6wkLHjvlLl2dU0bdKIpk0baflrwsTpXLsWCWifYyCTyVjxy0LGDPuc1OQ0Tvodxs/nDLeK1B2jxg4lOyuHnu0HYa+qO6ZNnoedgw1GRob07z6M0sal8TvvykkXbxJVdYdMJmPl6u8Z6TiJlOQ0fAKPcto7UCPPjh43nKysbDq3GYDD0IF8t3QOX3w2C7lczsZtvzDti/mqeKpIbm4epUoZsXnDLkKCLmNoaIiz2y769+/FqVOBmn4cqPTjhfOeyvxb1I+ffkxmVjZNmnRj5IjB/PTjQsaMVfpx6bJfadq0EU2b6j7fRiaTseznBYwfPpXU5DRO+B7Ez+cst+OK1LVjHMnJekLvDg4MGtKf+Uu+YfrkBQx06ItRKSNse4yktHFpToe4cPK4N2XKmDBq3FCG2Iwj91Uue45uxOdUoF5817tvd11m/qO8za5BH5grQANBEOoAScDHwOiCm6IoZgNVC34LgnAGmCOK4tXXBfrOIwaCICwVBGHOX3huuSAIfd/1uX8TgiAs1Ke+Nm1bkHDnHvcSEsnNzeXEcU9s7fpoyNgO7I3TIVcA3E+convPzm8MN/RqBGlpj97qHRq2akhKQjJp91PJy83jnPs5Otl00pCJuhDJyxcvAbgZFktV86q6ggKgZZtm3Lv7gAf3ksjNzcPd1Yd+ttYaMv1se+Fy5CQA3id96dKjAwCiKGJiYoxcLqd06VLkvsrj6ZOnAJhZVKeXTXecDih90bZdS+7cuce9hAfk5uZy/JgnA+00k5+tXV8OH1TKu7n60NO60HcDB/Xl3t0HxBb5yEpLe0RkRDSg/PiMuxlPNTNNW5u0bkxiQjLJ91PIy83Dzy2AHv27asikJqYRf+MO+fl/fSCycatGJCckk6KKlwC3M3S10ez1T0tM486Nu+Tnl1x89bTrzuXAK+r4K45pq3pkJaSRc/8R+bkK4k5epK5NWw2Z3KfP1f83MCkFora+hg5diDt5Qet6+/atiI9P4O7d++Tm5uLs7I69vY2GjL29DQcOHAPg+HEvevVS+vPZs+ecP3+Fly9LXk9Vr15tqlevQuzlwoPH6rdqQGpCCg8fpKHIzeOCezDt+nXUeC7mwnVevVAeIHY77CaVzasAoMjNI+9VHgCGRoYIMu2R3DbtWnC3SNpzdfHEVivt9eHIYWXaO3nCh+5F0p6tXV/uJTzQaMSCshevtHFp5HI5JibGlCtfVsN3TkfdsLfXHMGwt7dh/35nAFxcPOndq5vqen+cjrrx6tUrEhIeEB+fQIf2rQF4+fIlWZnZJfq0KKNGOXDE6YT69+jRQ7kQ4sHVK6fZtPFnZDLtKmawfX+OlqC7KA1aNSAlIYW0+2nk5eYR7H6ODjaa8XT9QhSvVGk3LuwmVVTxBBAVEsnzImnzr9KuVXMqlC/3l55t3bY5CXcecP+esgx3O+5F/4G9NGRsbHvjfNgNAE+303TrqSxfe/buwo3oOGKu3wQgMzNbq8yoU7cmVatV5tJ5zYb939FbFMdhA3Fz0Rw1Kp5njzqf1Jln96vzrKdWnn3xUnd58zpatWlGwt37xeoOTZv62Vqr6w6vk7507aFML8q6w6RI3ZHLE1XdofRXC+7eua/21wkXL/oP7K0Rdv+BvTmq8peH2ym1v6x7dyXm+s0i8ZRFfn4+z5+/ICToMgC5ublERcZgaWlesh+Puun2Y0H+Pe5JL1X+VfuxhHIbtOtaD9dTWnVtX1trXI64A+B90o8u3QvqWjAxKV3or9xcnj75k3oN6xAeGsWL5y9QKBRcOh/KpC/G6MV35hZmJdr6/yuiKOYB04BTwA3gqCiK0arv7cF/NVy9TSUSRXGxKIp++tL3gdBrw8DcwpSkpFT17+SkNMzNTTVkzMxNSUpKAUChUJCT84TKlZU9LTVrWREQ5Iqb5346ddb8mHtbqphV4VFy4cmnj1MeU8W0SonyNqNsCA0suTFqZl6dlCI2pSY/xKyYTabm1UlJTlXb9CTnKZUqV8T7pB/Pnj3nUowfIRGn2L5xL9lZOQAs/nEeq5auVVec5hamJCWmqMNMTkrF3EJTj0URGYVCQU72UypXqYSJiTHfzPyCn1euL9GOGjUtadGyCdFhNzSuVzOrysPkh+rfD1MeaTUeXodRKSN2eW1hu/tGrQZFUaqaV+VhSmHj7lHq49c2yEqi12Br/E8Elni/jFklniZnqH8/TcmgrJn2iaTNJ/RlfPBvdF34MWcX79O638C+I3Fu2g0DCwszEhMLRx+SklKw0IqnQpmCNF6lytudijpqlAPOzu4a1yqZVSY9pTBNp6ekU8lMe9pCAdaj+hJxpnDaXWXzqvzs8zsbLu7g5JbjGqMFAObmpiQnFsm3ydppz9y8WNpT5VsTE2Omz5zCr6s2aMinpqSxcf1OwqPPEH0rhJycJyQnp2r5zrJY5WlhacaDIr7Lzs6hSpVKWOryu6XyWVEU2bNnHfXq1mbypDEl+sXYuDT9baw57qr8cGzcuD4jRwyme09H2rW3QaFQMHq09jQtC4vCdwJI1NANSw4sZ7XnWqyH9+FxsmY8va7s6TuqH9cCdY98/VOYmZuSnFRYDqUkp2mVd2YW1UlOKizvcnKeUKlyRerWqw2iyMFj2/A548zU6dpTZxyG2XHyuM971VsU+yEDOFGsYVA8/nSmu7+YZ7dv+43Ll3z49lvtU7DNzE1JSUorZlN1bbuT09R6C+oOr5O+PHv2jCsx/lyIOM22InUHgLl5oS8Kwi5e15oX8aky7CdUrlyRuvVrIwKHXbZz+qwL/5uuPU2pfIVy2AzoRWBgsPqapYU5iQ8K4ygpKRWLIg0HpYwZiUXKieycnLcu+8zMq5OSrOkvU3PNab6mRepj7br2BRejfQkO92b7xn1kZ+UQdyOeDp3bULFSBUobl8a6bzdq1a6hF98FndWuP/5p/gW7EiGKopcoig1FUawniuKPqmuLRVE8qUPW+k2jBfCWU4kEQVgEjEe5+vkRECoIQj2U+6dWA54BU4AUIAKoK4piviAIJsBNoC6wHfAQRfGYIAjtgT+AMsBLoI8qjFWANVAK2CiK4tbXvNM8YBzK9R/eoiguEAShFbAFMAHigc9EUcxUDZ9cAnoBFYFJoigGCYIwERiskq8HuIqiOK8EfasAY0EQwoFo4A7wWBTFP1T3fwTSgEhgOZAONALOAV+p/GEDLFPZFw98KoriUy1lhTq1ronFemNLkklLfUjrpr3IzMyiRaum7Du4kW6d7Hj65M+S1JX0EjrC1y1qPaQX9Vs0YMHI+a8J7q/b1LJNMxQKBZ2a9qNCxfIc9dxN8NmLNGhUj8ePM7gecYOOXdu9tR7dtoksWPQNmzfu5s8/n+m0oUwZE/Yd3Mi383/g2VNNmbfS+xqGdBjF47R0LGqas+HoGuJj75J0L1lLTtCx5uhd9ABUrl6Zuo3rcOVsyeWEbnu05aL2+hG114+Gjp1pP90Rv1mFWde0VT1yn78i42ai1nN/Jz28DSNGDOazz2ZQG8PC8HSt1yohuG5DelK3eX2Wj1qkvpaR8pj5A2ZQqXolZm3/lste58l+XNjD/pdtQmT+wuls2bhHK+1VqFge24F9aNu8N9nZT9i1bx3du3fUDuOtfPf6d+xp7YiRkSEe7geZOnUisTdvExSsvf31oEE2nL9wVT2NqHevbrRp3Vy9LsHYuDSPHj3Weu51ur8dNo/MtAwqVKnAzyd/48HN+zrlitNziDX1WtTnu5Hf6rz/T6HDVO040pkeReQGctp3asPA3qN4/vwFR0/sJCo8muBzhXHhMNSW6V9qry/4O3oLaN22Oc+fv+DmDc2Rq7dL32/WX5yJE6eTnJxK2bJlcDqyjey0TI47FWnUv41NJci0atOMfEU+HZr2pULF8jh77iH47EUe3Esq2SbeLi8ZyOV07NSGAb1G8Pz5C5zddhMRHk3wuYsAyOVytuxYzY6tB7h7936R8N7Gnr9Rzr8+el8bfss2TclXKOjczIYKFcvh5LGLkLOXiL91l63r9rDPZTPP/nxObHQc1XR0SH0I392/p11/SHwY3jhiIAhCW5TzlloDQ4H2qlvbgK9FUWwLzAE2qeYzRQAFq8nsgVOiKOYWCc8IcAK+EUWxJdAXeA5MArJFUWyv0jFFNW9K1zvZAo5AR1UYv6hu7QPmi6LYAogClhR5zEAUxQ7AjGLXWwGjgObAKEEQii7kUCOK4gLguSiKrURRHAPsBCao3kem8tFBlXgHYLYqzHrAUEEQqgLfAX1FUWwDXAW0VtQU3Zoq4d5tLC0Le2IsLE1JTX2oIZ+SnKoenpTL5ZQvX47MzCxevcpVV9iR4dEk3L1Pvfo63fla0lMeU82iMONXNa9KxsN0LbmW3VoxatooVkxarp5qoYuU5DTMi9hkZlGdtGI2pSanqYcN5XI55cqXJSszG4fhtpwLOE9eXh7pjzO4eimcFq2a0rZjK/oOsCYozIv123+mS/f2jBs/Akurwt4XC0szUlM09SQnpapl5HI55SuUJTMji3btW7JsxTwios8w9auJzJozlSlfjAOU0zn2HtyIs9NJPE6e1rLvYcojqlsU9mJVN6/G4zRtf5VEgWzy/RSuXQinYbP6OuUepTyiepHen2pmVUlPfXs9AL3sexLsE4IiT1GizNOUDMpaFPamlzWvzJ9pmSXKx7ldpG5/zdGpBg6duKVjtACUvY1WVoUL0SwtzUkpFk9FZQrSeEbGm+e0N2/+EQYGcsLCojSuZ6SmU6VIZVbFvAqZaRnFH6dZ1xY4ThvO6sk/6UzTmQ8zSYx7QKMOmufJJCenYmFVJN9a6Eh7ycXSXvlyZGZk0aZdS5Ysn8u1qAC+mDqBGXO+ZNLnY+lp3YV79xJJT88kLy8PD/fTWFqYa/kuOSVNQ09SYgo1iviuQoXyZGRkkqjL76rexRRVGHmKPE64edO+fSst2wFGjRysMY1IEAT2H3CmXXsb2rW3oWmzHixfsQYHhwHqxcpt27QgKanwnQCsiuguiIfs9GwiQyIwr1OYh6uYVyHjoXY8tejWkuHTRrJy0g+vLXv+CVKS0zR6gc0tTLXKO6VMYXmnLMOzSUlO42LIVTIzsnjx/AUBvkE0a1mY1po0a4SBgZyoiBiK83f0FuAwVHsaEaAVfzrTXVLqO+fZZNUo8dOnf3LE6QSt2jTTuJ+anIa5ZWFPtNImzSmxKclp6hFHzbpjIGcCQtR1R+ilMFq0alpEd6EvCsLWlWctitS15VR1bXJyGhdCrpCRkcXz5y/w9z1HiyLxtPqPZdy5c4/tmzVHUhOTUrCqURhHlpZm6pFyDZki5USF8uXfquxT+uuhxkiluYUpD4v5K7VIfVzUX4OH2XLWv6CuzST0UjjNWyltOnrwBIN7j+Zj+0lkZWZz6+Ydvfvu30K+Hv7+Cd5mKlF3lD3pz0RRzAFOAqWBLoCzqgd9K1CQwp1QfmiD8mPZqVh4jYAUURSvAIiimKOaJ2UDjFeFdwmoAjQo4Z36ArtFUXymCiNDEIQKQEVRFM+qZPYCRbd8Oa76NxSoXeS6vyiK2aIovgBigFpvcohKZwKQrtoj1gYIE0Wx4MvssurACQVwGOiGcjV4EyBEZeMEXbpEUdwmimI7URTbRUfepU692tSsZYWhoSGOQ+3w8QrQkPfxCmDU6CEA2Dv2V7e0q1SppJ7fW6u2FXXr1eZewgPelbiIOCzqWGJawxQDQwN62Pfgkq9m72HdpnWZtnIaKyYtJzv99XOTI8OiqV23JlY1LTE0NMB+yAD8vM9qyPj5nGHYx8rpcbaD+3FBNdcwKTGVzqo5kMYmxrRu15z4W3f5dcU6ujS3oXvrgXw9ZT7ng64wavgU6tWrpfbd0OF2eHv5F/OdP5+MUfrOYcgAzp1V+m6gzSe0bGpNy6bWbN60hzWrN7N9634A1m9aSdzN22zasEunfTfCY6lRxxLzGmYYGBrQ16E3QafPv9HPAOUqlMXQSNmzXaFSeVq0b8bduHs6ZWMjbmJZxxIzlZ7eDtac9323odbeDr3wdyt5GhFAWsQdKtY2o3yNasgM5TQc3Im7vpq7WVWoXVj51O7TiqyEIpWbINDArqPO9QUAV69GUL9+HWrXroGhoSEjRtjjUWwhpYeHL2PHKnekGTp0IGfOvJ0/R4504OhRrdFU4iNuYVbHnGo1qiM3NKCzfTdCfS9ryNRuWofJK79i9aSfyCmSpiubVcGwlBEAZcqXoVG7xqTEa47ohIVGUbduYb4dMswOH620F8DHnyjT3mDHAephcvsBo2nTvDdtmvdm6+a9/L56Czu3HSAxMZl27VthbFwagB49OxMUdFHDd6NGOuDhodlY9fA4zbhxysXnw4bZEXgmRH191EgHjIyMqF27BvXr1+HylTBMTIwpW7YMADJBRr++PYmOvqnlw/Lly9GjeydOnizcwCAgMJihQwZRrZpyuk+lShWpWdMSNzcfdWMh9Fok7h6nGalDdynjUpQuYwxAKeNS1KhfA5NyJlRXlT3d7HtwpVg81Wlal6kr/8dPk1a8sez5Jwi/dp069WpSo6YlhoaGOAwdyGlvzTx32ieQEZ8ozySyc7AhRDUicNY/hI+aNlSvK+nUtZ3G4mGHYQO1pvm8D72gbOQNcrDBzcVbK2xlnq2tTncjRwzWmWfHqfOsHWdU6a4k5HK5eoqMgYEBA237aI1URIRFU6duLZVNyrrD1/uMhkzRumPg4H6cV9cdKer588q6owXxt+4W8VcUdevVomYtpb8ch+nwl3cgI1X+GuTQnxBVXXvGP5iPmjbCWBVPnbu2Vy+8nb/oG8qVL8f3C1aW4MfC/DtypINuPxbk37fwY1EK61oLDA0NGDSkP34+mv7y9znLsI+VO83ZDu7LhaArACQnptKle3uVv0rTql0L7txKAKBKVWU8WVia0X9Qbzb8vkPvvpP4sLztrkTFx65kQJYoirq6kk4CKwVBqAy0BQKK3Rd0hFdw/WtRFN+8VU7JYbyOglU6CjTtLrp6p/i9N7ED5f6wZkDRL8Xi7yaifGdfURS1968sAYVCwbdzlnP0+A5kcjmHD7hwM/Y28xdOJzzsOqe8Azi4/xibtv3K5bDTZGZm8/lnyh2JOndtz/yF08nLU5Cfr2DOzCXqBYWLl89l2PBBGJsYExFzljNH/Tm09pDOd8hX5LPl+80s378CmVyGr5Mv9+PuM2bWWG5F3eKy7yU+WzSJ0ialWbBZOYz/KPkRKyYt1xmeQqFgyfyV7HPejEwuw/nQCW7djGfmgq+ICo/Gz+csTgdcWbv5RwKvuJOdlcPXk5Wzu/bvPMKv65dzKuQ4ggDHDrkRG3OrRD3zZi/D5cRu5HI5B/c7E3vjFt9+9w3h167j7eXP/r1H2bLjN0Ij/MnMzGLSxBk6wyqgU+e2fDx6CNHXYzl3XvnBufvXfVwIKKxQFYp8fvtuHb8f+kW5faqTN3fjEpgy51NuRNwk2Pc8H7VsxKqdKyhXoSzd+nVm8uxPGdP7U2o3qMX8VbPIF0VkgsD+DYc1djMqHi/rvt/ALwdXIpPJ8HY6RULcPT6dM4GbEXGc971Ao5YNWbFjKWUrlKVzv058Oms8n/ZR7nhkamVKNYtqRFyIfK3NoiKfs9/vZfCBecjkMmKczpIRl0TH2cN4GHmXu77XaDHRhhrdmpKfp+Bl9p/4zSycRmTZsTFPa/TOOwAAIABJREFUUzLIua97sbtCoWDGjO9xd9+PXC5n714nbtyIY/HiWYSGRuHp6cuePU7s2vU70dHnyMjIYvz4aernb94MoVy5chgZGWJv359Bg8aqd0cZPnwQDg7aW8rmK/LZs3g73+5bgkwu58xRPxJvPWD4rE+4G3mbUL8rjF44kdImpflmkzLtpSc/YvXkn7Csb8XY7z5FFEUEQcBjmxsPbmrGkUKhYMHc5Ti77kQml3No/zFuxt5mwaLphF+7jo93AAf3OSvzbbgvWZnZ6p3ESuLa1Ujc3U4REHSCvLw8oiJvsHXbfm7dvoun5yHkMhl79joRExPHkiVzCA2NwMPDl127j7BnzzpuxASTmZnFmLHKrSVjYuJwPuZOZEQgeQoF079ZRH5+Pqam1bh8yYcyZUwwMDAgJ+cpFhZmfD5FOWK2bbuygezoYIuv3zmePStc3Hvjxi0WL/0Fb6/DyGQCubl5TJ++iPv3kzRsiYmJ49gxd6KK6a5YrSLztymnbMkN5ASdOMud6HiW7F+GTC7D38mPB3H3+WTWGG5H3eKK72UmLPqU0ialmbtZOZ3mUfIjVk5Sbt/447FVWNazonSZ0my/tJuNc9cRfi7stX7Wxdwlq7gSFklWVg59HMfy1aRxDCu2yLskFAoF3837kUMu25DJZTgddCUuNp45304jIjwaX+9Ajux3Yd2WVQSHepOVmc1Xk5R7e2Rn57Bt0168/J0QEQnwDcL/dOFOVfaO/Rk3cup71wvQqUs7UpLTdE7fKMizHu4HkMvl7FHn2dlcC43Ew9OX3XuOsHvX78REB5GRkcW48YVbcd68eZ7yRfKs3aAx3L+fiIf7AQwNDZHLZQQEBHN4n4uW3sXzf2Kf82bkcjlHVXXHrAVfERkeg5/PGVXd8RNnr3iQlZXNNFXdsW/nEVavX4FvyHEEQcC5WN2hUChYOPcHDrvsQC6XcfjAcW7G3mbewq8JD7vOae9ADu0/xoatP3Phmg9Zmdl88dlsdTxt3bgHnwBnRFHE3/ccfqfPYm5hysy5XxJ3Mx7fc0pb1m/cxe7dhzX86OlxEJlcxt49TsTciGPJ4jmEXlPm3927j7Bn9x/ExASTmZHF2HGFW8PG3bxA+fJKPw6274+d3WiNHY0UCgVLF/zMXudNyGQynA+5cevmHWYsmEpUeAz+PmdxOniCNZt+IOCyG9lZOUyfosxH+3c58cu6ZfgEH0MQBI4dLvTXpt2rqVi5Inm5eSyZt4qMjEy9+G7XNt3fKP8k/1SP/odGeNN8NUEQ2gB7gI4oP5qvoRwhGAqsFUXRWVBOIGshimKE6hlnlEcvPxFF8SvVtT2AB8qGQywwShTFK4IglEM5legzYCAwQhTFXEEQGgJJoihqTYoXBGEAsBjltJxngiBUVo0aRADTVOsHlgIVRFGcWXSLJtWUnquiKNZWrTFoJ4riNFW4HsBqURTPlOCLTKB6wdQo1bSoKMAQaCCKokIQBGvAG+XowD3V/7ehXGsQCvQWRfG2av2FlSiKcSX5vlqFRnrZDatjBd3TVT4E0X/qZ55g1st3XEvxF2lcQefMsw9CaUE/uwsPFUzfLPSemPvo3JuF3gNDTNvoRY9vpva0jg9F9gv9pHF9bclnb6afOAI4eu0Pveip3UD73I//6zx+nvNmofdA8e1KPyQvFblvFnoPZDx/ohc9AFblXn+e0PviWV7Ju8K9b1KzbrzFclz9sdVq7AcvHr9IPKB3m9/4pSGK4jVBEJyAcJQfukGqW2OAzYIgfIfyw/gIyvUFoJw+5IxyIXHx8F4JgjAKWC8IgjHKRkFflL3vtYFrqobGI5TrCHS9k49qofFVQRBeAV4odwyaAGxRfXTfAbRP9Ph7bAMiBUG4JoriGJUtgShHT4pO1L6AciF1c5QNAlfV4uOJwGFBEEqp5L4DSmwYSEhISEhISEhI/PsQ/1XNlPfHW3VBqrZA+lHHrQElyB+j2Jp4URQnFvn/FZRz7ouzkLfcElQUxVUoP76LXgvXFa4oitZF/v8Y1RoDURT3oBwNKbg36A065wPqLXdUi447AcWPA34miqLW6VWiKAZQuHhbQkJCQkJCQkJC4l+D3s4x+K8hCEIT4DbKxcu6J7pLSEhISEhISEj85/iv7kqkn0nLfxFBEJoD+4tdfimKovYG3u9X7yWUZw0UZZwoiup9D0VRjEF5PoMGqvUJZz7k+0lISEhISEhISPxz/FcXH/+rGwaqD3Hdm2h/WL0ftOEhISEhISEhISEh8W/jX90wkJCQkJCQkJCQkPi3oa8d2/SN1DD4F6OvbUSvZMe/Weg9oa9tRPXFtfTbbxZ6Tyjy9TNwGWP87gfh/VWM5PopgpxTruhFTyXjsnrRA/qrlEobGOlFz9nMWL3oAf1tI5pwy10vegCMLbrrRU8Zo9J60XMr4qBe9ABM7LpYL3rijB/rRQ/AjWz9lOPbKnbTix4J/SE1DCQkJCQkJCQkJCTegfz/6Hal0q5EEhISEhISEhISEhLSiIGEhISEhISEhITEu/Bf3ZVIGjGQkJCQkJCQkJCQkJBGDCQkJCQkJCQkJCTeBWnEQEJCQkJCQkJCQkLiP4s0YiAhISEhISEhISHxDvxXzzGQRgz+j9KmZ1u2BG5l27ntDP9qhNZ9x8mObPLfzPpTG/jx8I9Us6z22vB69elGyFVvLoad4uuZU7TuGxkZsm33Gi6GncLb34kaNS0BqFHTkoTUcPyDXPEPcuWXtUvVzxz32EfIVW/1vapVKwNg08+aqMgzxEQHMWfOVzp0GXFg/yZiooMIOneSWrWsAKhcuSKnTjmR/jiW39eu0HjG/eR+rlw+Rdg1Pzas/wmZTPZB9BTgcmwX10L91L8/pK5zZ93IyY4nNiaYeXP/pzPsQwc3ExsTzPlgd3XYAPPnTSM2Jpjo6+ew6dcTACsrC/xOOxMVeYaI8AC+njZJLX/o4Gb8g1y5FHaaxMdR3H8Y+V7SQ5myZdTX/INciblzgRUrvwWgb78ehIb5ER4ZwMzZX+q0b/fedYRHBhBw5jg1Vbratm1B8AUPgi94EHLRk0H2NupnNm7+mfiEy0TFnCU0zE9vvgsMOsGVMF+SH18n8WEU00vw3fbda7kcdhof/6MavrufGkFg0AkCg07w69plABgbl+bQ0a2cv+JN0EUPduxey4WrPnqxCeDLLycQG3ee9MybJCaHM6uEONq7bz0RUYEEnnVVx1Gv3t0ICjnJpcveBIWcpGfPzupnRoyw59Jlby5e8sbVbQ+Vq1QCoE/f7ly6doqr4X58M+tznbp27vmdq+F++AYcU/uvAEsrc+6nhDNtuqYdMpmMM8FuHHbeBoB1n26cu+xBcKg3/5sxWWc8bd65muBQb9x9D2NVw0J976OmDTl56iAB593wC3GlVCkjypQ14fQ5F/Vf1O1gZGWqaIX7Or77aQ097D7Gcay2j0tCMDTGoKKVXtJDy5ZN8Qs4RlhkAGmPY4iJDWbmrC906ty9dx1hEQH4B7qo00Obti0IOu9O0Hl3gi94qPNs/QZ11NeDzrvzIDkcWVlt3wVfDsN+wnQGjpvGjsOuWveT0x4xec5Shk6exaezFpP6KF19b83W/Th+NoPBn37Dyg07EcWSP+ta9GzN6oANrDm7CfupQ7XuD5w8mF/81rHKZy0LDy2jqqp+rWpZjR89VvOT1xp+8f2DPmP6l6gDoHOvDrgEHcT1/GEmTBujdb91p5YcOL2Tiw8C6WNnrb5uZmXK/lM7OOi7C6cz+xg23kFn+P369SQs3J/IqDPMnj1V674y324gMuoMZ86eoGZNZdro3bsbwSHuXL7sQ3CIu0a+LeCo83auXDmldd3cugX2Qb8yOOQ3mkwr+byQGnbtGZN8gMot6ijfpVJZ+jgvZOStHbT7cXyJz0l8eKSGwV9EEAQzQRCOCIIQLwhCjCAIXoIgNBQEwUcQhCxBEDxKeG69IAhP/45umUzG1B+msmTCEr7qM5Weg3tQo0ENDZn46DvMtJvB1/2nEewZwqcLP3tteKt+W8zo4VPo3mEQQ4bZ0bBRPQ2Z0eOHk5WVQ6fW/dm6aS/fL5utvnfv7n36dB9Cn+5DmDdzqcZzX02Zq773+HEGMpmMP/74gcEO42nZqjejRjrQuHEDjWc+nfgxWVlZNGnanXXrd/DjDwsBePHiJcuWrWbBgh+0bBg9ZirtO/SndZu+VK1aheHD7T+IHgAHhwE8/bPwoLYPZROAo6MtTZs24t69RJq37MWoUY589JFm2J99+gmZmdk0btKN39dtZ+VPiwD46KMGjBzpQItWvbEbNIb165QNpry8PObOW0bzFtZ07WbP1KkT1WGOHjOVfj2HgQBOh06wbs2295Ie/nz6p/pan+5DSHyQjKe7LzKZjN/WLGPYkE9p37Y/w0fY06ix5sF+4yeMJCsrh1YterNxwy6WrZgPQExMHD27OdCt8yCGOk7kj/U/IJfLATh44BjDh07C3NyUYUM+1Zvv+vQciqjy3R9rtjFk2CAt340ZP4KsrBw6tLZhy6Y9LF42R30v4e59enV3pFd3R+bOXKK+vnH9Lrq0t6Vvz2H0H9ibdWu36cUm655dsBvUl9zcXNq27kuHdv0ZMWIwjYvF0YSJI8nKyqZl815sXL+TFT8sACA9PYMRwyfTsYMtX0yZw/adawCQy+X88utiBtqOplNHW65HxTLl87HIZDJ++W0pI4dOpnN7W4YNH0SjRpq6xqrSXrtWfdm8cTdLl8/VuP/TqkX4+56jOF9+NYG4m8rDHGUyGT/+uoixI76kV6fBOA4bSINi8fTJuGFkZ+fQra0t2zfvY9HSWep3X7d1FQtmL6d3FwdGDJpIbm4efz59hk2PYeq/xAfJiO94oKPjwH5sWaO7LCgJedmq5OWk6iU9rPppEb/8vAEBmDVzMXcT7jNMZ54dQVZWNq1b9mbTxt3qPHsjJg7r7o5072LPMMdP+X2dMs/evnWX7l3s6d7Fnp7dHHj+/AX5z3M0wlQoFPy4bgebVi7CbddavAOCiU/QPMRr9Za92Pez5viONXw5bgR/7FAekhYeHUtYdCwu23/DdccarsfGczUiWqc/BZmMT1d8zi8TVjC373S6DO6GZQMrDZmE6Dt8N2gOCwbM5LLXeT75Vvkhm/kwkyVDF7Bw4Cy+d5jP4KlDqVi9kk49MpmM+T/NYvqYOYzoOY7+jn2p07C2hkxqYhpLv/mJU65+Gtcfp6Xzmf1UxvT7jIkDv2DCtDFUNdVsSMlkMtasXc4Qx4m0bdPvtfm2RXNrNmjk20yGD59Ehw4D+HzKbHbsXKvx3GCH/vz59JkO3wm0/2kCgWN+wcN6HrUdOlG+gYWWnEGZ0jSe1J/HoYUHhCpe5BL56zHClh/S6a9/I/nCh//7J5AaBn8BQRAEwBU4I4piPVEUmwALAVPgV2BcCc+1Ayr+Xf0NWzUkJSGZtPup5OXmcc79HJ1sOmnIRF2I5OWLlwDcDIulqnnVEsNr07YFd+/c515CIrm5uZw47sUAuz4aMgMG9uHooRMAuJ84RTcdPQhvQ/v2rYiPT+Du3fvk5uZy1Pkk9kV6egHs7W3Yf+AYAMePe9KrV1cAnj17zvnzV3jx8qVWuE+eKNtaBgYGGBkZUrdurQ+ip0wZE775ZgorV6774DaVKWPCooUziIyMITc3Vxn2UTcG22v2Qg22t2H/fmcAXFw86d2rm+p6f44edePVq1ckJDwgPj6BDu1bk5r6kLDw6wA8ffonsbG3sLQwU4dXkB569emGy1H3954e6tStRdWqlbl4/irt2rXkzp17JCQ8IDc3F5djHtgN6qchbzeoL4cPugBwwtUba+suADx//gKFQgFA6VKlKNoBeD7kClZW5rx6lasOW1++S7hzT+W7k5w47oltMd/ZDuyN0yFXte+6v8F3z5+/ICToEgDNW3zEo4cZyA3kerHpiy/G4+npR/ztBBISHpCcnMaxY+7acWTXj4MHlHHkWiSOIiNiSE15CCgbcqVKlcLIyAhBEBAEARMTEwDKly9LaupD2rZrwd0797inirPjLp7YDtL030C7vhw5dBwAtxM+9LAu9N/AQX1JSHhA7I1bGs9YWJjRr781+/ceBaB12+Yk3HnA/XvKMs/tuBf9B/bSeMbGtjfOh90A8HQ7TbeeyjK2Z+8u3IiOI+b6TQAyM7PJL3YqeZ26NalarTJi3gvehXatmlOhfLm3lhcMSiEqciE/Ty/pQRRFWrZsyp0793jx4iUpyWkcP+aBnV1fDZ0D7fpy6KAyjk64etNTFUcaebZ0KZ299tbWXbh75z4ocjWuR8XepqalGTUsTDE0NMS2V1cCz2ueaH7nXiId2zQHoEOrZkXuC7x8lUtuXh6vcvPIU+RRpZLuqrh+qwakJaTw8EEaitw8LrgH07ZfBw2ZmAvXefXiFQC3wuKobK78KFfk5pH3Kg8AQyNDBFnJX3ZNW3/Eg4Qkku6nkJebx2k3f3r21zxFOCUxlds34snP1/RTXm4eua+U/jEqZYhMpv0p165dK+7EF5atx465M2iQZr00yM6mSL71UufbiIhonfkWlPXS119P5uef12vprNK6Hk8S0nh6/xH5uQruuV2kRv+2WnIt5w0nZpMHipeFcax4/pJHl+M0rkn8M0gNg79GLyBXFMUtBRdEUQwXRTFIFEV/4EnxBwRBkKNsNMz7u8qrmFXhUXLh0eqPUx5TxbTkIWubUTaEBl4t8b6ZhSnJSSnq38lJqZiZm2rImJtXJ0klo1AoeJLzhMqVlQVrzVpW+AUdx9VzPx07axYCf2z8Cf8gV2bOVQ5jWliY8SAxWX0/KSlF48OqQCZRJaNQKMjJeUKVKrp7XYri4X6AxAdhPHn6J7fi7nwQPUuXzOX337fz/PlzjXA+lC5f37NqvwMkJqVgUTxsy0L9CoWC7OwcqlSppPVeiUkpWFhqPlurlhWtWjbj0uUw9TUzC1PycvN49Cidu3fuvdf0ADBkuB1urt7KcCzMSEwsmvZSsCiuy8JULVPgu4JpJ+3ateTSFR8uXPZmxvTv1B8dANWrVyM3t7CS0YfvzC1MyVX57s6deyQnpWFezB4zc1MN3+XkPKFy5Upq3wUEueLmuZ9OOnxXt35tKlYqT9DZC3qxqUGDunTp2p6WrZric+oIbdq2ICkpVVunhSmJRWzK1pG+HR1tiYyI5tWrV+Tl5THjm++5dMWb23cu0bhxA/bvdcbc3EwjvScnpWr5z9zClKTE1EL/ZT+lcpVKmJgY883Mz/llpfYHy08/L2Lp97+oP+DNzDXLvJTkNK00bmZRneSkInpynlCpckXq1qsNosjBY9vwOePM1Onao7EOw+w4edxH6/p7R2YA+Xnqnx86Pcyas4Qvv5pIp87t+OHHBSxb8itJSamYWxSPIzOSiubZ7MI827ZdSy5e8eb8JS9mfvO9Rp4FGDp8EMeOuWuZ+vBxBmbVCju4TKtVIe1xhoZMw3q18Tt3EQD/4Ev8+ew5WdlPaNW0ER1aNaX3iCn0HjmFru1aUbeW5ihAAZXMKpOeUli/ZqSkU9ms5Pq116i+RJy5pv5d2bwKq3zWsv7idty3uJL1MFPnc9XNqpGW9LDQvpRHVDcruQOvOKYW1TnsvwfPUBf2bjjI47R0jfvKPKlZLxWPp6IyJdVLRfMtwOLFs1m3bgfPnmk3eo3NKvEsuTBOnqVkYGyuGV6lZrUwsahMkl/4W9v6byVfD3//BFLD4K/RDAh9x2emASdFUUx5nZAgCJ8LgnBVEISr95/eL0lI61JJ0yWth/SifosGuGx1eY1OHReLB1iCzrTUh7Rp2pu+3YeyZNEqNu9YTdlyZQD4asocrLsMZrDtWDp1aceIjx0QdIajqUvX+7xuPmgBg+zHUqt2O0oZGdGseeP3rqdFiybUq1eLkyc1K/wPYVOBrquhEW8Rtu64edN7lSljwlGn7cyas0Q94lLwrrXq1MD1mKdmgJpKdep8XXoowHHYQHXYb+MXAZ1CAFy9GkHH9gOw7uHI7DlTKVXK6HWvqAffCdSuU5Pjxzx0PleyTpG01Ie0btqL3t2H8P2iVWzZ8ZuG7+RyOV9OncDN2NvcS0jUi00GBnLKlDHB09OPRYtWsm//hneyqYCPPmrA8h/mM/3rRapwDZg8ZQxdOw+ift2OXL8ey8zZX/6NOBNZsGg6mzfs5s8/Nac42AzoxaNH6USEF04d+TvpTm4gp32nNkz7fB6OtuOwtetDtx4dNcQchtpywsVL+3k98CHTwxefj+fwQRdcnN1ZuOBHNmxapQ5PU2fJ7xV6NYJO7W3p1XMIs2Z/qZFnDQ0NGWjXhxOu2r4TdSz1LG7DnC/GczUymhFfzOFqRAzVq1ZGLpdxPymFO/eT8HPair/TVi6FXedqZIz2S6I73ksqq7sO6Umd5vXw2HpCfS0jJZ0FA2Yys8dUegzrRfmqFXQ++5pi7a1IS37IJ30m4tj5YwaNHEDlqpof4G9TL+kuxzXz7YofFvD118qpry1aNKFuvVq4n9ReW1CSTo1oEwTaLh3LtWX/d6YL/f+I1DDQA4IgWAAjAO2urGKIorhNFMV2oii2q1m2pk6Z9JTHVLMo7Fmoal6VjIfpWnItu7Vi1LRRrJi0XD28qYuUpDQsLM3Vvy0szUhNfagpk5yGpUpGLpdTrnw5MjOzePUql8zMLAAiw6NJuPuAevWVi4kKhiL/fPonx509aN22BUlJKdSwKpxzaGlpTnJKmoaupKRUrFQycrmc8uXLkZGRVeL7F+Xly5d4ePrSuFH9966nU8e2tG7dgps3zxPgf5wGDepw+vTRD2JTga41vy3D3r4/DRrUwd/XGStLc1KKh51YqF8ul1OhQnkyMjK13svK0pyUZOWzBgYGODtt5/BhV06c8NYILy31EbVr18DtuLJyfl/pAaBJs0YYGBgQqfpIS05KxcqqaNozJ6WYruTkQpmSfBd3M54//3xGkyaNCu1Ie4ShoaGm/R/Yd6mpD6lVuwYn1L4z1eG7VA3flS/Rd/c1fLfmjxXcuZPAk5zCAckPbVNSYgo+3gFYWZoTejWC/Px8Gjasq60zKRWrIjZVKBJHFpZmHDqylc8nz+buXWVnR4uWTQDUv4+7eNKhY2uSi/im4Nni/ktOSsXSyqzQfxXKkpmRRdt2LVm6Yh7h1wP58quJzJz9JZM/H0vHTm2wHdiH8OuB7NjzO917dOLjccM0yjxzC1PSdKTxgh70wnjKJiU5jYshV8nMyOLF8xcE+AbRTGUPFKRxOVERuj883yv5ecpRAxUfOj2MHzcCN7dTWFqZ43rcizZtW2BpaUZqMZ3KOCqSxiuUI1NXnn32XCPP9rPpSUR4NI901GemVauQ+qiwJz/tUTrVi/VuV69amd+XzcN562qmT/oEgHJly+AffJkWHzXAxNgYE2NjunVoTWRMnE6XZqSmU6XI1NvK5lXITMvQkmvWtQWO04bz2+SVOuvXrIeZJMbdp3GHJlr3QDlCYGpZvfDdzavxKO2xTtnX8TgtnfibCbTu2FLjujJPatZLBXVyAclFZIqXrRaWZhw+spUpk2ep82mHjm1o3bo5MTeC8fN3pn6DOvQ9tkgd3rOUDEwsKqt/m5hX5nlq4YiJYdnSVGhsRV+XRThcWkvVNvXouWeWegHy/zVEPfz9E0gNg79GNKA9zl8yrYH6wG1BEBIAE0EQbr/+kZKJi4jDoo4lpjVMMTA0oId9Dy75XtKQqdu0LtNWTmPFpOVkp2e/Nrywa1HUrVeLmrUsMTQ0xHHoQE55BWjInPIKYORoRwDsHfsTrBqurVKlknp+Y63aVtStV4t7CQ+Qy+XqqSUGBgb0G2BN7I04rl6NoH792tSuXQNDQ0NGjhiMh4evhi4PD1/GjR0OwNChdpw5E/La9y9TxgQzM2UBK5fLGdC/N8HBl967nm3b91OnbjsaNepC7z5DuXXrLjY2Iz+ITQW66tXvyKNHj0lISGTAwNGMHOmAu8dpDVl3j9OMG6fcmWrYMDsCVWG7e5xm5EgHjIyMqF27BvXr1+HyFeWUgO3bfuNG7G1+/2Oblu5y5cqSL+ZjaGjw3tJDAUOH22mMRISGRlK3Xm1q1bLC0NCQYcMH4eWpudDOy9OfT8YMA8BxiC1nVdNoatWyUi82rlHDggYN63LvfmFP+vWoWIyMDNVh68N35cuVQxTzMTQ0VPnODp9ivvPxCmDU6CFv4bvaat99+90Mylcoy5eT51KnXm1q6skmt5OnMDOrTr36tenRszNGRobY2vbRjiMvP8aMVcbRkCJxVKFCOVxcdrF08S9cvFg4yJqcnErjjxqodyrr3acbcXHxXAuNom4R+4YOs8PH019Dl7eXPx+PVu4U4+A4gKCzSv/Z9R9Nq2a9aNWsF1s27WHtb1vYse0AK5b+RrPG3WnVrBeTJ84g6NxFJoz6ijr1alKjprLMcxg6kNPegRp6TvsEMuIT5W4vdg42hJxTlrFn/UP4qGlDShuXRi6X06lrO26pFjUDOAwbqLfRAjHvJYLcEGQGekkPySlpGBuXpl692owc5cDdO/cZOnwQXl6aceTl5c/oMco4chxiy7mS8myDOhp5dvgIe445a08jAmjWuD73klJITEkjNzcX78AQrLu015DJzM5RTxfbcciVIQN6A2BevSpXI2PIUyjIzcsjNDKaujV1TyWKj7iFWR1zqtWojtzQgM723Qj11VzLUKtpHSatnMpvk34ip0j9WtmsCoaqEZAy5cvQsN1HpMQn6dQTEx5LjTpWWNQwx8DQABuHPpw7FaxTtjjVzatRqrRST7kKZWnZvjkJ8ZozDEJDI6hXv7BsHT7cHk9PzXrJ08u3SL4dyNmz5wGoUKE8x112s6RYvt2x/QD163WkyUfd6NtnBLdv3cVv+I/q++nhdyhXx4wyNaohM5RTy6ETiacLp1nlPnmOS7OpuHWMIGO2AAAgAElEQVSciVvHmTy+Fs/ZiWvIiLz7VnZL6AfpHIO/RgDwkyAIU0RR3A4gCEJ7wEQUxbPFhUVR9ATUkzcFQXgqimL94nJvS74iny3fb2b5/hXI5DJ8nXy5H3efMbPGcivqFpd9L/HZokmUNinNgs3KLSEfJT9ixaTlOsNTKBR8O2cFR47vRC6XcfiACzdjbzNv4ddEhF3nlHcgh/YfY8O2X7gYdoqszGy++Ey5Q0enru2Zt/BrFHkKFPkK5s1cSlZmNiYmxhxx3YmhgQEyuYygMxc4sMcZhULBjBnf4+F+ALlczp69Tty4EcfixbO5FhqJh6cvu/ccYfeu34mJDiIjI4tx4wu34Lt58zzly5XDyMgQe/v+2A0aQ0ZGJi7HdlGqlBFyuYwzZ86zZes+4uMT3que2NhbWr4r8N/7tqlAl0KhYPny39iwYRXXI8+wZ68TMTFxLF0yh6uhEXh4+LJr9xH27llHbEwwmZlZjB6r3C41JiaOY8fciYoIJE+hYPo3i8jPz6drl/aMGzucyKgYrl5RfkR8//0qvH2UH7CDh9hycN+x95oeChg8xJbRwwu3oFQoFMydvRRXt73I5TL273Mm9sYtFn03g2vXovD28mffXie27VhDeGQAmZnZfDphOgCdu7Rj5qwvyc3LIz8/n1kzFpORruyd2rXnD7p174hMJiMsMoCMzCzWr9/5wX3nMGQAB/Yd4+jxHcjkcrXv5i+cTnjYdU55B3Bw/zE2bfuVy2GnyczM5vPPZirt6dqe+Qunk5enID9fwZyZS8jKzMbcwpRZc6cSdzMe38BjIIp4+znx5MnTD54edu85wu4dvyOXyTjuupvMzCyOH/fkxo1bfPf9TK5di8LL04+9e5zYsXMtEVGBZGZmM3H81wB88eUE6tarxfxvv2b+t8prDvbjSU15yMqf/uDUaSdyc/O4/yCJr6cuQKFQMG/OMo6d2IVcJufg/mPExt7m20XfEBYWhY9XAAf2ObNl+2quhvuRmZnF5E9n6syXr0OhUPDdvB855LINmVyG00FX4mLjmfPtNCLCo/H1DuTIfhfWbVlFcKg3WZnZfDVJuXtUdnYO2zbtxcvfCRGRAN8g/E8X7oJk79ifcSO1t4Z8G+YuWcWVsEiysnLo4ziWryaNY5j967e8VDx9jEEFM72UD19+OZc/1v4AAqzf+BPp6Zns2nGI2Bu3WPjdDMJUeXb/3qNs2/EbYREBZGZm8dnEbwDo1LkdM2d/QW5uHmJ+PrNnLlHnWWPj0vTq1ZUZ0xfptNNALmfh15P5cv4PKPLzGWLbm/q1a7Bh9xGaNqpHry7tuRIezR87DyIg0LZFExZNV25D269HJy6FXWfo5FkICHRt3wrrLu106slX5LNn8XYW7FuCTC7jzFF/km49YPisT7gTeZtrflcYs3ACpU1KM32Tckes9ORH/DZ5JRb1rRj73UREUUQQBDy3neDBTd1TghUKBb8uXMv6w78hl8s4ecSTO3EJfDF3EjciYjl3OoQmLRvz664fKV+xHN37deHzuZ8xyno8dRrUYsaSaWo9B7YcJj72jlb4s2ctxu3kPuRyOfv2HdWRb4+yY+caIqPOkJmZxQR1vh1P3Xq1WPDtdBZ8qyxvB9uP49Ej7ZGcooiKfK4u2kvvQ/MQ5DLij5wlOy6JFnOHkR5xl6QijQRdOFxai2FZY2RGBtTo3w7/T1aRcyv5tc/8k+T/R08yEN5m7raENqrpQb+jHDl4ASQAM4BdQGOgLJAOTBJF8VSxZ5+Kolj2TToG1bTTS+RcyY5/s9B7Iusdt++TKESRr5+lSFWM335XlL/L87xXetHzLFd716cPQSXjN2br90bm87+16/FbU9rA6M1C7wEjuf76qYz1ZFPCLd293x8CY4vuetFTxqi0XvQ8ij3xZqH3xMSui/WiJ+7Vu08V+qvcyH7wZqH3wLaK3d4s9J4Yk3zgH9rAUzc/1hrzwb/RFt07qHebpRGDv4goisnASB233lg6v02jQEJCQkJCQkJC4t/JP7Vr0IdGWmMgISEhISEhISEhISGNGEhISEhISEhISEi8C//VifhSw0BCQkJCQkJCQkLiHZCmEklISEhISEhISEhI/GeRRgz+xfg/uq4XPQ0qWLxZ6D2h82TED8DjZzl60VPVpLxe9ACk68kmfW7B9lKRqxc95YyM9aLnycvnetGjT17qaeeol3mv6GnaTC+6bjxNfLPQe0BfOwUBPE8O0oueOg0H60WPSd0BetEDIJfpp49UX+UQQK6i5ENN3ycTHge+Weg9MUZvmt6O/H/VHknvD2nEQEJCQkLiH0dfjQIJCQkJiZKRRgwkJCQkJCQkJCQk3oH/6gFn0oiBhISEhISEhISEhIQ0YiAhISEhISEhISHxLvw3xwukEQMJCQkJCQkJCQkJCaQRAwkJCQkJCQkJCYl3QjrHQEJCQkJCQkJCQkLiP4vUMPiX069fTyIiArh+/Sxz5kzVum9kZMT+/Ru4fv0s586doGZNKwB69+5GSIgHV66cIiTEg549uwBgbFya48d3Ex7uT2ioLytWzNept2uvTpwMPoLHBWc+mzZO637bTq1wOr2Ha4lB9BvUS329UdMG7PfYxvGzBzkWsJ/+Dn1ea1+vPt0IvuLFhWs+TJsxWYd9hmzdtYYL13zw8jtCjZqFZy581LQhHqcPc/aCO4EhbpQqZaQOLzYmmHlz/6fTX4cObiY2Jpjzwe7UqmWlvjd/3jRiY4KJvn4Om349AShVqhQXQjwIvepLRHgASxbPVstv27oa/2BXAkJO4OZ9gPOh3u/NDmPj0hxw2kLQZU+uRPpz484FbsQEM7cEmw4e3MyNmGBCitk0b940bsQEc/36OfqpbAK4FXeRsGt+XL1ymosXvNTXly6dy5mQk1wJ8+Vechihkf5MnzlFpz3bd6/lcthpfPyPUqOmJQA1alpyPzWCwKATBAad4Ne1y9TPLPx+BuHRZ0hIuqYRlk0/a6IizxATHcScOV/ptO/A/k3ERAcRdO6k2r7KlSty6pQT6Y9j+X3tCq3nAFyO7eJaqJ/W9T59e3D52mlCI/yZMesLnTp37v2D0Ah/fAOPqe0rwMrKnAepEUybPknr2X79ehIZGUh09LkS7dm/fyPR0ec4d86tmD1HePz4BmvXLtd4ZuTIwVy9elqdn6Ojz723NA6wfdtvJCdGEB7mr77W38aa27cu8iQnngf3w3B13UO5cmU19LxruqtQoTxHjmwjKuoskZFn6NSxrca7j/hiOH4PTlG+kvJ8kPbW7dh9Zgd7g3bz8VcjtWxt3rEZm702cOquF90HdtO4N2XhJHb4bWNnwHb+t0y77CyKdZ9unLvsQXCoN/8rIf9u3rma4FBv3H0PY1VDmX+HjLDj9DkX9d+D9CiaNvt/7J13WBTX97jf3WXB3pVq7x0E7IigoFJEscYSNVFji0ajxphYkmgSk1iiUWPvsRekKoooWEEBFcSCIB0bYFfK/f2xuLDsYguS7+/zzOszzyMz556z59wzZ3funbnTRK2vuPrIzMyEY0f3cuVyIBHhAXw5KT/vWrduzukgT/QqmaKoaIpMz+CNvgJ8//MSujgPps+wcW+V1UXXbp04ed6T4FAfJk7RPgf09ZWs2vAHwaE+ePr/kx+v/s4cOblPvcXfv0yzFo012noc2UFMyqWPnt8Ac+dM405sKBfO+3EtKpjbMReKtQ55Ht5GyIUjhF06xl8rfkZe6H0J9t1tOHfRjwvh/kyeOlZnHNdvWsaFcH+OBOzVqLMJaZc5EezBiWAP/ihQZ1/rjIoKZsb0Ir4vtq8iKiqY4KBC5+2MiURFBXP1ykmN83by5NGEhx0n7NIxtm39CwMDAxwdu3L/3jWePYkjMSGMdWsXo6enp2GnuPrpdY4D4UAo0FbLsf+AXMRH3/4LpAuDD0QmkxnJZLJdMpksRiaTRclkMh+ZTNZIJpP5yWSyDJlM5lVIfrNMJouVyWTheZv522zI5XKWLfsJN7cRWFh0Z8CA3jRp0lBDZuTIQaSnZ9KihS0rVmxg4cJZADx4kE7//p9hbd2DMWOmsXHjUnWbZcvWYm7ejfbtnejQwYrO9u217M7+5WvGD5lGny6f0KuvA/Ua1dGQSUlK5fspP+F70F9j/4vnL/juyx9xtx3K+E+mMvPHryhfoRy6kMvl/PLHHIb0H0uXdq707e9Mo8b1NWSGDO9PRkYmHdr0ZM2qrXw/fzoACoWClWt/Y+a0+dh2cMXdZQQ5OblqfS1b2zFoUB+aNtWM12ejPiE9PZMmzTqzbPk6fvn5OwCaNm3IwIFutDK3x9llKCuWq4r4y5cv6e44EEsrByytHOnh2JV2bdsA8PX0+XTr3JfuNu40adYQH69jxeJHVpbqxTSr/9qIbXtXcnNyiIuNZ/qM+QwuwqeM9EyaNuvMn8vX8XMBnwYNdKO1uT0uBXx6TXeHAVhZO9K+g5N63+LFq7G36YOQwcoVGwk8cYa+/Vy0/Bn66QAyMh7R1sKRv1dtZu4P09XH4mLjsbPpg51NH2ZMnafef8T3BD3sB2jlwJ9/LqC326e0Nrdn0EA3rRwfNXIwGRkZNGtuw/IV61m4YDYAL1685Icf/mDWrAXows2tJ0+ePtXaL5fL+X3JfAa4f057q570G+BC4yYNNGSGjxhAZkYmlq27sXrlJub/NFPj+MJF33HM/5RO3X/+uQA3txGYm3dj4EDd52xGRibNm3dhxYr1LFjwbQF/FjNr1kINeYVCwR9/zKdHj0G0a9eL+vVr4+sbUGw5DrB16x6cXfJfHySXy1n+50IeZT6mt9sI7t69z4Xzl/j66/Eadt4375Yu+ZGjR07QsqUtlpYOXIu+qdZX3bg6ljYWpCWmqT/DlwsmMvvT7/ncfgx2bnbUalhLw9e7Sff4bdpiAg5pvmSpmWUzmls1Z6zjOMZ0/4LGrRvRun0rrf56bWfh798xbMA47Nr3pk8/JxoWyvdPhvcjM/MRnS17sW71Vr6bPw2Ag3u9cezSD8cu/Zg8bhYJ8Ulci7qh1ldcfZSdnc2MmT/QslVXOnV2Zfz4kWqdv/78HT8tWEJ2RhK5zx4iL1tFp58F6ePkwN9LdJ83b0Mul7Pgt+8ZPnA8dh1649bPiYaN62nIDB7mTmbGIzpbObFu9TZmv47XPm962Panh21/poz7loT4JKKuXle3c3J1oEnTBiQmJH3U/C7In8vXqWtgt+79i7UODRk6Huu2PbBo051q1ari1reXRhwXLZ7HoH5j6GTthHv/oupsJm3NHfh75Wbm/TBDfSwuNh67zm7YdXZjel6dLaizdWs7Bg1yo2lhP0YNJj0jk2bNOrN8+Tp+Xqjyo2kTVfzMze1xcR3G8uULkcvlmJgYMXHiZ7Tv4IxFm+4oFAoGDXLjzz8X8PX0+VSs3JC0tPsYGlbn88+GfJR+ep3jgDkwF/hNZ2dKFAvShcEHIFO9vvcgECiEqC+EaAbMBgyB3wHtIXYVM4QQ5nlb+NvsWFubExMTR1xcAllZWezd64mLi4OGjIuLAzt27AfgwAEfunbtBEBERCQpKXcBiIq6gYGBAfr6+jx//oJTp84CkJWVRXj4VQyNa2jobGHRjPjYRJLik8nOysbv0DHsenTRkElOSOXmtRhyczXvsrtzO4H4WNVbRe+l3efh/XQqV62k0z8Ly1bE3o4n/k4iWVlZHNrvQw8new2ZHk727NnpAYCXxxE626ouYrradyLq6nX1l0p6egatLVpo6Nuzx4Perj009PV2dWTbtr0A7N/vjb1d57z9Pdizx4NXr14RF5dATEwcba0tAHj69BkASqUeekolQqiu4h8/fqL248njp2Q8zCwWP3Jzc3n+/AWngy5gYdmK27fvEBoSjpFhDXbv8cC1kE+uRfjk6tqD3UX4VBSPHz+hjWUr4m7f4eXLl+Tk5HDogDe9nDVnfno52bP7n4MAeB46go1thzfqBbgYGkFa2j2Nfa9zPDY2XtVnew/j6uqo7d/2fQAcOOCNnZ0qx589e86ZMyG8ePlSy1bZsmWYMmUMv/yyXOuYpVVrbt++w5288+rAPm+cnLtr+ufcnZ07VP55HPTDtmu+f04u3bkTm0D0tZsUprA/e/d66vRnu9ofHy1/Xr58oSEvk8mQyWSULVsGa2tznjx5yrVrN4o1x4OCz/MwPUOto621BTExcdSpU5MTJ4LZvceDcuXL0bdv/kXk++Zd+fLl6Ny5HRs37QRU9SczM/9t3uPnfcHahRvU51dj88YkxyWTEp9KdlY2gYcD6eSomWdpiWnERseSKzTrkBACfQN99PT1UOorUSj1SL+frtVfABaWLYm7naCuGx4HfOjhZKch49jLnr1556+3x1H1+VuQPv2c8Njvo6WvOPooNfUuYeFXAXjy5CnR0TcxNTFS+1q+QnmVYpkccnJ0+lkQK/OWVHzd5j0xt2xJXOzrOpuNxwFfHHtp1jtHJ3v27ioQry7ttPS49XPCY7+v+u8yZUvz1YxxRF29TlZW9kfN78J8rDr0+jtCT08Pff387w6ANlatiC1Qhw7u96aXVh3qxq6dqjp0+JAfNl3fXGcL69yzx0O3H6/jd8AbO/V566gVP2tr1filnkKP0qVLoVAoKF2mNBUqlCcmJo4tW3ar7QghMDMzVtspzn7SyHGoCCS/MRAlhCiB7b9AujD4MOyALCHE3693CCHChRBBQojjwOPiMGJiYkRiYor676SkFExNjXTIqM6RnJwcHj16TNWqlTVk+vZ1IiIiklevXmnsr1ixAk5O3TkXFKqx39C4OmnJd9V/p6XcpYZx9ff+/C0smqFUKkmIS9J53Ni4BslJqeq/U5LTMDY2LCRjSHJSitq/x48eU6VKJeo1qIMAdu5fx9GT+5k4+XMtfYlJKZiYFIqXqREJBeKVmfmIqlUrY2KSv1/dNi/Wcrmc0JCjpCRd5vjxU1wICVPLLVu5kH/2rUFPT8GGtduLxY/CMbp/7wGOPe0IOBGsyoF39Mm0QG6AKn9e+ySEwNdnJ+fP+TL6c80RmomTP6Nte0v6DXBl0cI/SU7S9sfI2JCkAv48evSYKlVUeVerthkBQQfx8N5G+w6at4oUpnDcdfr3DjlemPnzZrBs2TqeP3+udczYxJCkAudVclIqxiaa/pkUkMnJyeFR5hOqVK1MmTKlmTL1Cxb9sqJIf7RirqX7/fzJzs5m8uTvCA09yqFDW9DT02PTpl1A8eW4lh95OiIjr+Pq6khSUgqdOlpT08xES6awnaLyrl692ty//4AN65cScuEIa/7+nTJlSgOqAY77qfe5fe22ul01o6rcTc6/kLyXcp+qRtWKjFNBrl26RvjZCPaE7mTPxZ2EnrxI/K0EnbJGBc5NUJ2/RoXz3SS/trzus8pVNAc8XPv25NB+Hy19xd1HtWubYd66BecvqOrQtOnzWPTL9+hVroWibFVynj18pxh9KMbGNUgpUGdTk9MwLjS4ZFRARhWvJzrj5XEg/zbGGbO/5GTAaVKS09T7PlZ+F2TC+FFs27qS2rVrUqlSRaD46hCAl+d2EhPCePzkKYcP+an3GxsbkpyYH8fkZO06ZGxcqA5p1dlDHPbZTvsOVjp1JiWlYmJqrKHTtMDvipycHDIf5cXP1Fjz90ZiKqYmxiQnp7J02Rpibp0n/s4lHmU+JjkplcSEAudMShrW1hYcOZI/c1ec/fQ6x4EE4A/g2zc2kPhXSBcGH0YL4OIHtFsok8kuy2SypTKZTOeNoDKZbKxMJguVyWShubkvtI4XHHHIk3+jTNOmDVmwYBaTJmmeRwqFgi1bVrBq1SaS4gtdfL9F57tQrUZVfl4xl7lfLSiyrc7Pzrv4B3oKBe3at2HimBm49RxKL5fuNG3e6K2fuyh9b4pjbm4uVtaO1K5rhbWVBc2b598T+9XE75jx1TwyMx/j5p4/Tfxv/OjcJX80UqFQ0MmmLevXbCc2Nr7YfLLt2oe27Xri4jqM8eNH0rlz/ojewf0+HNzvzf69nnw+dth72BSkpd7Forkd9jZ9mfPdr/y9fjHlypfVkn2bHk0Z7XZvysdWrZpRv35tDh/203n8XWwWdQ7M+m4Kq1duUs8ifYjud7JfAD09PcaOHU779k5MnDiL9PQMZs6cWGTbD8mHwryWHT12GuPHjWT+vOkolXq8epX1wXb0FAosLFqyZs1WrNv24OnTZ8ycOYnSpUvx7azJbFm89a1+8I51yKSOCbUb1GRw26EMsh6CRcfWtGzXoghfdZkpFFPe/FksLFvy/PkLrl+79W76PrCPypYtw57d65g2fZ56NPqLsZ/y9Yz5ZKfHk/P0AYpy73bx9MEUQ45bWLbkxfPnXL92C4BmLRpTp24twsOufqDu9z+vAP5es5VGTTry7eyFPH/+nEWL5rzBrnb7d/ledHEdRu06Vhjo62NTYKbpg2sFqjpr3rwr9jZ9mDP7F9ZsUNXZf1N/ivKvUqWKuLo40qhxB2rXsaRs2dLY2GjOAH366UCSk1MJPn3hLXY+rJ9e5zhQE5gKbHhjgxIitwS2/wLpwqDk+BZoAlgDVQCdT/0KIdYKIayEEFapqRkaU3OmpsYkFxhNAdXIhlneKJ5CoaBChfI8fJiRJ2/E7t1rGT16mvpH5WtWrvyVmJhY/vpro9ZnSEu+i6FJ/giQoXEN7qXef2dHy5Yrw8rti1mxaC2XL0UWKZecnKYxUmBsYkhqyt1CMvkjHgqFgvIVypOenkFychpnT4fw8GEGz5+/4Lj/KSpXrqShz8zUmJSUQvFKTFGPeioUCipWrMDDh+kkJaVojIaamRprjFwBZGY+4uSpM/Rw7FpIZypPnzzDOW/K9t/60ap1M3W7foNcyc0VrFut+tFkampM8jv6lFggN163fe3T67jcu/eAQx6+6iljUI2gm5oasX+vFy69HTExNSQ1VdOflORUTAv4UyHPn1evskjPmwq+HB5JXGw89RvUpSgKx12nf0mpRea4Ltq3s8TCohXXr58h4PgBGjasi6fvDk3/CpxXJqZG2v1VQEahUFChYjnSH2ZgZd2aH36aSURkIOMnjGTa9PGM+SL/zsEkXTEvpPtN56wuWuflw+3bd0hKSuHp02e0b6+aiSnuHC+s4/r1GJych7Bu/Q5Onw7h9u24t9opKu8Sk1JITExRz7jtP+CNhXlL6tevQ506tVhzZDXbz2yhunF1/vZdycsXL6lhkj9TWd24Gg/SHhQZp4J07tGRqLBoXjx7wYtnL7hwIpSmFk11yqYkp2mMqhqbGJKmle/5tSo/3zPVx93cVbcR6dJXXH2kp6fH3t3r2LnzIIcO5d+C8+nwARw8qLItXj1FplfqnWL0oaQkp2FcoM4amRiSmnqvSBlVvMqRUSBevd17cajAbUSW1ua0bN2MH3/5lh5O9tSrX4fj/ns/Wn6/5u7d++Tm5pKYmMyjR4+xtlLVweKoQwV5+fIlXt7+GrcKJSenYmKWH0cTEx11KLlQHapQnvSHeXU2z3ZEXp1t0KCulk5TUyNSklM1dKrOz3ydFStU4OHDDJISUzR/b5gZkZySSjf7zsTFJXD//kOys7M5dMgXE1MjzGqqZOd8P5Ua1auxd+9hzXgVYz8VzHFgL/9HHj7+X0W6MPgwIoE33yNRCCFEilDxEtjEOyR2aGgEDRrUpXbtmiiVSgYMcMXbW/NhX2/vYwwd2g8Ad3cnTp48A6huEzpwYBNz5/7G2bOatwrNmzedihXLM336D+giMvwatevVxLSWMXpKPXr26U7g0aB38lNPqceyTYvw3OuLv2fAG2XDL12hXv3a1KptilKppE8/J476aj5EeNT3BAM/cQPAxa0Hp0+dAyDweDBNmzdW3/fYoZM1gQGnNfQNHOiGp9dRDX2eXkcZPlz1AGy/fs6cCDyt3j9woBv6+vrUqVOTBg3qciEkjGrVqlCxomqFlFKlStHN3obr12MAqF+/jtqP+g3qkJZ2t1j8uJGn/5vvppCVlU1OTo7ap0ED3fAq5JNXET55eR1lkA6fypQpTblyqlH8MmVK49DdlshI1TMODRrUJezSFerWr8MnQ9yJuRVLH3dn/Hw0+9LPJ4BBQ/oC4NqnB8F5/lStWln9IFntOmbUq1+HO3G6b+GA1zlehzp1VDk+cEBvvLw0c9zLy5/hw/oD4O7uTGCef0Wxdt026tazonHjjth3c+fmzVhce+XfLnXp4mXq169NrdpmKJVK3Ps74+ujuQqGn89xPhmq8s+tb09OnVT55+T4Ca2bd6V1866sXrWZJX+sZt2abYX8qav2Z8AAV53+DFP740Rg4Jk3+pOcnEaTJg2pVq0KoaER1K9fl+TktGLLcV2EhIbToEFd2rRppc67Bg3qsnZtvq/vm3dpafdITEymUSPVA5b29p25du0GV69GY2rWmmEdRzCs4wjupdxjXK+JhASGYlrHFKOahugp9ejauytn/M+9MVavuZt8j9btWiFXyFHoKWjVviXxt+J1yoZfukrd+rWoWUt1jrm56zh//U4wIO/8dXZz5PSp8+pjMpkMFzdH9f3yhfUVVx+tW7uYa9G3WPbnWg1dySlp2HZR3XsuU5aC3Cw+JhGXrlK33mv/9HBz74W/n2a8/H1PMGBwgXgFacfr8IH8C4Ntm3Zj1dyeti27c//+QxLiE+npNOSj5fdrjIxUA2ChoRE0a9aYuLiEYqtDZcuWUetXKBT07GHPzRv5t8qFXbxCvXp11HWobz9n/LTqUACDP1HVod59ehJ0UvV8oGadrUm9+nWIi0vQ0jlwoJtuP17Hr4AfXl7+WvELCQknPiGZdu0sKF1adcFpZ9eZoKDzNGhQl+nTJ9DD0Y6cnJyP2k8FcxywB7Qf8PoP+F9dlQghhLS95wbIgPPAmAL7rAHbvP93BbwKtTEu0HYZ8Ovb7JQqVUu4uY0QN27EiJiYODF37m+iVKlaYuHCZeSE7gsAACAASURBVKJfv89EqVK1RMWKDcX+/V7i1q1YERISJpo06SRKlaol5s37XTx58lSEh19VbzVrWoj69dsKIYS4du2mev+8qQtFS8P2Gtv4IVNF7K07Ij42QSz/ebVoadherF68QXw5fLpoadheDO4xSqQmpYlnT5+J9AcZ4mZ0jGhp2F7MmjBPvHqVJa5dua7e+tsPV+s1rNhEYxvSf6y4dTNWxN6+I37+cakwrNhELF60UgwfPF4YVmwiatVoJQ4f9BW3Y+LEpdAIYd2qu7rthDEzRHTUTXEt8ob4a9l6DX23bsWK7+f8KhRKE/HTgiXCre8IoVCaiDLl6oq9+zzFzZu3xYULl0SDRu2FQmkiFEoT8f2cX8WtW7Ei+vot4ewyVCiUJsK8TTdxKeyKiLgcKa5cvSbmzf9NKJQmQk/fVJw+fUFEXb0urkXeEMEnz4nbMXHF5od5U1shhBDXo2+J2Ng74sWLF+Lu3Xvi+zm/Cr08n/r0HSH0lCaibCGfGjZqL/SUJkJPh096ShPRsFF7ERERKSIiIsXVyGi1Tj2lidh/wEtERV4XcbEJ4smTpyL+TqJY+OMSUa1CI/H7r3+JoYPGiWoVGgnT6i2ER54/F0MjhGUre1GtQiMxctgkcS3qhrhy+ZqICL8qhgz8QlSr0EhUq9BILF+2TiQlpoicnByRlJgiFv28XOgbmInevYerc3zO3EVC38BMLFi4VLi7jxL6BmaifIX6Yt8+T3HrVqy4cCFMNG7SUegbmAl9AzMRGxcvHjxIF48fPxEJCcmiVWs79TF9AzPRsFF7cfVqtKhUtr7GNqDvZ+Lmjdvidswd8dP8P0SlsvXFol+Wi08GjBWVytYXhlWaioMHfETMrTgRGhIuWjfvqqXjl4V/iu+//Vljn4FBTdG796cFztlFwsCgpli4cKlwd/9MGBjUFBUqNBD79nmp/WnSpJMwMKgpDAxqirhC/rRubS8MDGqKiRO/Fdeu3RCXL0eJ8+cviVu3ii/HFUoTsXPXQZGcnCpevXolEhKSxegx04SL6zCRlnZPvHz5Sty790As+m3Fv8o7PaWJsLRyEKGh4eLy5UhxyMNXVKveVH2sm5mj6GbmKFLiU0Tflv1FNzNH8e3w70RCTIJIiksSGxZtEt3MHMXWpdvF96Pmim5mjmKC8yRxN/muePb0uch8mClio+NENzNH4VCrp/Dc5iXibtwRcdfjxN61+9T6u5k5CpNKzTS2YQO+EDF5dejXn5YJk0rNxJJFq8SITyYKk0rNRF1Dc+F50E/cjrkjLoVeFu1b5+vo5zxCXLwQrlNfcfVRF1s3IYQQEZcjRVj4VREWflW4uA5THwu9GCFys16InFfPxauHCeLVvZg3blMmjBEdO7QTzZo2FTadOoidG1e9tc3rzbRyczF8wLi8eMWLX3/6U5hWbi6W/rZKjPxkojCt3FzUM7IQnof8RGzMHREWell0MO8hTCs3F6aVm4v+LiPFxZBw9d+Ft68mzBYvX7z86PmtUJqIbdv3ictXotTnVUxMXLHVIbOa5iIkJFxcvhwlIiOjxcqVG0WNSk1E1fIN1dugfqPFrZu3xe3bd8SCHxaLquUbit9/XSGGDvxCVC3fUJhUay4OHfARMXl1tk1Le1G1fEMxYujE/DobdlUMGTBWS+etmFgxZ86vQqlvKhYsWCr6uo8USn1TUa58PbFvn6e4medHo8YdhFLfVCj1TcWcOb+KWzGx4vr1W8LFdZh6/08/LRHR0TfF1avXxPbt+0TZcnWFa+/hIjc3V7x69UokJ6eKsPCrIjDw9Efpp9c5LoSIEEKcF0JY/te/A4UQTK09SHzs7b/wS5b3Y1XiPZHJZCaofuBbAi+AOOArYCOqW4bKAQ+Az4UQR2QyWQBQHdWFQTgwTgjx5E02SpeuXSKd07CiyduFiom7L95t6vXfcv/Zo7cLFQPVylQoETsAD0rIp0qldS8v+zF49FL3vfrFTZl3WNu9OHie/ertQsVEdu7bV58pDnTcevxRsDXU/QzAx+Dak8QSsZP2tGTqHcDz5Heb1f231G3Uu0TspD7RvYrUx0AhL5mbJ8rrly4RO1BytTW3BH9DZr9KKqly9E5MrTP4ozu/NG5Xifus93YRCV0IIZIB7TfugE0R8va69ktISEhISEhISEj8X0C6MJCQkJCQkJCQkJB4D/6rVYM+NtKFgYSEhISEhISEhMR7IP6zV5B9XKRViSQkJCQkJCQkJCQkpBkDCQkJCQkJCQkJiffhf/VWImnGQEJCQkJCQkJCQkJCmjH4v0xWTnaJ2Ln3IvPtQsVEZgktoVZW/+O+/fM1xqWqlIgdgMr65UvEzv2XJZcPJbVccik9/RKxU5LLlZYUMlnJrJYX+bjoF+EVNw9fPC4ROyVVh6DklhGNvXH47ULFgHG9niViB6C8smSWEc0SJbPEMJTcMqIV9cuUiJ3/i/xnLyD7yEgzBhISEhISEhISEhIS0oyBhISEhISEhISExPvwvzlfIM0YSEhISEhISEhISEggzRhISEhISEhISEhIvBfSMwYSEhISEhISEhISEv+zSDMGEhISEhISEhISEu+B9B4DiZKkJ3A9OiqYmTMmah3U19fnnx2riY4K5kywJ7Vrm6mPfTNzEtFRwURePYWjgy0ABgYGnD3txcVQfyLCA5g392u1/NYtKwgK8eZChD/X489z9pIfk74arcOmkr83LubMJT+8j+3CrJaJ+ljT5o3wPPoPgWcPE3D6EAYGqqUh/9m3hmPBBwg8e5hFS+Yhl6vSzcHBloiIAK5ePcn06eN1+rdt219cvXqSU6cOUauWyj97+86cPu1FSMgRTp/2wta2o7qNh8cWzp/35eJFf5YvX4hcLqdb9y6EXvInLCKAqdO+0Gln05blhEUEcPzEfmrVMgWgjWUrgs54EnTGk+CzXri4OgLQoGFd9f6gM54kJIczZMxALb0d7dpxMHgnHmd3M2rSMK3jbdq35p+jGwlJPEl3l67q/cZmhuw4soFdxzaz7+R2+n/aR6ttQTrbtcfnzF78zu9n9Jefah23am/B/mNbuZJ8BkcXe41ja3f9yfmbx1m9fYlO3fbdbDgb6seFsKNMnjpG67i+vpJ1m5ZyIewofsf3UDMvdjVrmRKfGsGJoEOcCDrE70t/ULeZPecrwiMDiUu6pNYfFRXMjOm6c3zH9lVERQUTHKSZ4zNnTCQqKpirV07ikJfjAJMmfU7YpWOEhx3nyy8/19D32dihXIwM4E5aONFx54otx/d7bSYoxBv/oAP4Bx2gevWqODjYcvnyCSIjTzF9+gSdvm3btpLIyFOcOuWh9q1KlUocObKL+/evsXTpjxptfvrpGzIzb5KZeYvLlwOpWrWyls73qQkAPRy7Enn1FIXrzITxI4mOCib7VRLRUcEafdSlSwdCLhwhPOw4x4/tf+8+mjx5NOFhxwm7dIxtW//CwMBAw48Fv31HbMolgkK8OVOMtUhXPzk6dOXK5UCiIoOK7Kft21YRFRlE0KnDhfppNw/uR7Ns6U8abY4e3cOVy4FcOO/HhfN+VKtetUTq0PgJIwHo2q0TJ897Ehzqw8Qpn+uwpWTVhj8IDvXB0/8fzGqqYte3vzNHTu5Tb/H3L9OsRWONtht3rODY6YNaOt/G9z8voYvzYPoMG/febQHsu9tw7qIfF8L9mTx1rE6f1m9axoVwf44E7FXXoteYmhkTlxzGxC8/U+8bN3Ekwee9CTrnxdqNS9A30KeLfUeOn/fgRIgn46Z8VtgM+vpKVqz/jRMhnhw8uh3TvNjp6enxx8qf8A3ah//Zg4z/SrOtXC7H68Ru1v+zAijZPurW3Ybzl44QGn6MKdN0xU6fDZuXERp+DP+AfTpjF58SzqTJ+Z8z/OoJgs95cfL0YY6fPADwUWIXFOaDb9A+vAN343H8Hy2dEh8P6cLgA5HJZEYymWyXTCaLkclkUTKZzEcmkzWSyWR+MpksQyaTeRWSl8lksoUymeyGTCa7JpPJJhehWgGsBHq1bG3HoEF9aNq0oYbAZ6M+IT09kybNOrNs+Tp++fk7AJo2bcjAgW60MrfH2WUoK5b/jFwu5+XLl3R3HIillQOWVo70cOxKu7ZtANi58yC27VzJyc3h7OkQ1q7eQp/+TjRqXF/D5ifD+5GZ8YiObXqydtUWvp+vurhQKBT8tXYR30z7ga4detPPZQRZWar3L4wdNY3und3p2qE3VatVxrVPD+RyOcuW/YSb2wgsLLozYEBvmjTR9G/kyEGkp2fSooUtK1ZsYOHCWQA8eJBO//6fYW3dgzFjprFx41J1m2HDJtKuXS8sLR2oXr0q7v2cWbxkPv3dP6OtVQ/6DXClcZMGGnY+HTGAjIxMLFrbs2rlJn746RsArkXdoKtNH2w6utKvzyiWLV+AQqHg1s1YbDq6YtPRFdvObjx//oITvic1dMrlcmb98jWThnxNvy5D6dm3O/Ua1dGQSUlKY96Uhfgd9NfYfy/tASNdxzG4+0iG9xrDqC+HUd2wms4kkcvlzFk0k7GfTMG18yCc3XtQv1FdDZnkpFS+nfwj3geOarXfuHI730ycV6TuXxfPZXD/0XRq60zffi5a+TD00wFkZDyirYUjf6/azNwfpquPxcXGY2fTBzubPsyYmm/jiO8JetgPAFDrb93ajkGD3GhaKAdGjRpMekYmzZp1Zvnydfy8cDYATZuoctzc3B4X12Hqi8DmzRrz+Wef0LGTC5ZWjjg5dadBA1U8bG070sPJnqysLGzaumDboXex5TjApDEzcbBxx8HGnQcP0vnzzwW4uY3A3LwbAwfqzu+MjEyaN+/CihXrWbDgWwBevHjJDz8sZtashRrySqWSadPG0bVrX6pVa0qlShWYM2eahsz71gS5XM7yPxfi4jqMwnXmzNkQejkPISsrmyFDx6v7yNraghXLF+LebxTmFt3w9T32Xn1kYmLExImf0b6DMxZtuqNQKBg4MH/t/dbmzalYqTz6BvoM7f8Ftu1cP3o/9Xb7lNbm9gwa6KbVT6NGDiYjI4NmzW1YvmI9CxfMLtBPfzBr1gJ0MWLkZNq260nbdj15+CC9ROqQl+dR5HI5C377nuEDx2PXoTdu/Zxo2Liehq3Bw9zJzHhEZysn1q3exuz5qjw6uM+bHrb96WHbnynjviUhPomoq9fV7Xq5dOfZ0w97B00fJwf+XqI7Vm9DLpezaPE8BvUbQydrJ9z7F1WLMmlr7sDfKzcz74cZGscX/DKb4/6n1H8bGRsy5ovhdLd1x6a9C3K5nN79evHjb7MZOXACjh370tu9Jw0KxW7gsL5kZjzCztqVDau3M2veVwA4uTmgr69PL5v+uNp/wpAR/dU/fAFGfTGUWzduq/0pqT6Sy+X8tng+A91H08G6F/36u9C4sWbuDfu0PxkZj7Ay787qlZuY/6Nm7H7+9TuN2L2mt/NwbDv1pputO3K5/KPFbojbaJy7DsKt2xCtz/B/AVEC//4LpAuDD0CmeuPPQSBQCFFfCNEMmA0YAr8Dw3U0GwnUBJoIIZoCu4pQ3xa4BdzOyspizx4Perv20BDo7erItm17Adi/3xt7u855+3uwZ48Hr169Ii4ugZiYONpaWwDwNK9gKJV66CmV6hdL+foFYGHZkrjb8ZwJuoChYQ089vvSw0lzhLmnkz17dh4CwMvjKDa27QGwte/Etas31AUqPT2T3FzVBNuTx08B1aiAUl9l09ranJiYOOLiEsjKymLvXk9cXBw0bLm4OLBjx34ADhzwoWvXTgBERESSknIXgKioGxgYGKCvrxoRfPz4Sb4tpZK6dWtx+/YdtZ0D+7xwdu6uYcfJuTv/7FCNeBw66Itt1w4APH/+gpwc1YtoSpUy0PkSrq5dOxJ7O56UxDSN/S0smpIQm0hSfDLZWdkcOXScrj1sNGRSElK5eS2G3FxNvdlZ2WS9ygJA30D5xhdLtWrTnPjYRBLvJJOVlY3PwaPY9+yiIZOckMKNqFvq/ijIuaAQnj7R/UXfxrIVcbfvcCcukaysLA4d8KaXczcNmV5O9uz+RzUy5XnoCDa2HYr8rK+5GBpBWto95HK5hv49ezxwzRsNfY1rwRw/4I1dXo67ujpq5bi1tTlNmjTg/Pkwdd8FnTqHm5vqBUlfjB3OEZ8TxMbcIf5OImkpd4stxwvzOr9jY+PV+a3Lt+3b9wGq/LazU+X3s2fPOXMmhJcvX2jpzMnJ4cGDdLKysoiLS8DY2FBD5n1rQltrC43PWbDOhIdHYlijOtnZWdyJz++jb76ZxKFDviQkJAPQ1a7Te/URgJ5Cj9KlS6FQKChdpjQpKarzRy6XM+en6Xjs9yU3VxB/R2W3pPppz97DunNQ3U/eWv304uVLnboLYmnVukTqUEJCMuaWLYmLjc+LXTYeB3xx7KUZO0cne/bu8gDA2+Monbu009Lp1s8Jj/2+6r/LlC3NmAmf8ufiNW/1VxdW5i2pWOHDXs7YxqoVsbfvcCcvfgf3e9OrUPx6OXdj105VLTp8yA+brh0KHOvOnbgErkff0mijp6dHqbw8LFOmNOXLleVObAIJd5LIysrG86AfDr26arRx6GXH/l2ql7v5HvanY5e2gOoljWXKlEahUFCqlAFZr7J5kvd9ZGRSAztHG3ZvV32+kuwjy0KxO7Dfm14umnXcybk7u/5R5Z7HIT+6FIidk0t34uISiL52U8t+QVq3afFRYifx3yFdGHwYdkCWEOLv1zuEEOFCiCAhxHFA12s1xwM/CiFy8+TvFqHbFFC/AjQxKQUTEyMNARNTIxISVV/OOTk5ZGY+omrVypiY5O9XtzVVtZXL5YSGHCUl6TLHj5/iQkiYWs7I2JCUlLv0H9SbE8eDSUlOxci4hoZNI2NDkpNS1TYfPXpMlSqVqN+gNgLBzv1rOXpyHxMma04j7ty/liu3gnjy+CleHkcxMTEiMTFFfTwpKQVT00L+mRiRWMC/R48ea9060bevExERkbx6lf+m2cOHtxIff4knT55y82YsSRp2UjE20fwxZWxipJbJycnhUeZjquTZsbRqzbkQX86c92HqlDnqL+jXuPd3Yd8+TwpTw7g6acn5XZuWcpfqxtW15IrC0KQGuwO24HvxIJtX7uBe2n2dcjWMqpOalH9RkpZyF8P3sPMmjE0MScrra4DkpDStH6JGxoYkJRWI3aPHVKmiil2t2mYEBB3Ew3sb7TtYaumXyWQa+pOSUjExNdaQMS2QJzk5OWQ+ystxU2PN/ElMxdTEmMio69jYtKNKlUqULl2Knj3tMTNTjTw1bFiPdh3b0KJVMw54b6G1RYtizfGlKxfiH3SAqTPGaeSuyrcUTArl3bvkd0EMDasTHHyB0NCjxMaGUrFiBfUParXO96wJBeXV+wvUGRNTI7Kz83M+KSmV2rXNqFS5Iv5H93LurA/NmjZ+rz5KTk5l6bI1xNw6T/ydSzzKfMyxY6rRyAkTRnHU9wQGBpo/gD9mPyUU6ifTwnX2PfvpNevWLubCeT++/XYKJiaGJVaHjI1rkFLgvEpNTsNYK3b5MiqfnlC5SiUNGde+PfE44KP+e8bsL1m7cgvPn2lesJYExsaGJCcWqEXJOuJnbKgZv7xaVKZMaSZPHcPvv/6lIZ+aksbKFRsIjwwk8uZpHj16TGrK3UKxu4tRoZpnaFyDlOT82D3Oi53v4WM8e/ac81HHOB1xhHUrt5CZ8QiAuQtn8uv8peoL1JLsI2NjI3WNBtUMcuE6bmxiSFJiAVuZT6hSVRW7KVPH8tsvKyiMEIL9hzYRcOogI0YN0vi8xRk7IWDrvr85fHwnn3zaT+tz/F8gtwS2/wLpwuDDaAFcfM829YFBMpksVCaT+cpksoa6hJYsWeKwe/duN5lMFpqbqxpxLzxSpGskWYii9qva5ubmYmXtSO26VlhbWdC8ef69iTKZDOu25pw7E8r5syq3Co9NFaVbodCjbfs2TBwzE7eew+jl0p3OXdqrZT7pNxbzxrYYGOjTuUs7dA2Cv5t/+TJNmzZkwYJZTJr0rYZM796fUreuNQYG+jRv3kiHjsI+Ff1ZLoZG0N66F3a2fZn29Tj1vcqgurXDybkbhw76aCvQrVR7XxGkJd9lkP0I3DoMwnVgL6pU0/1DpKgcKA7eFv83yaSl3sWiuR32Nn2Z892v/L1+MeXKl32rzXfVX1SfRUff4vc/VuHrsxMvz+1cvhJFdrbqNhI9PQVly5bhiG8AP875g7WbVc9VFEeOTxwzE/tOfejTaxjtOljSpUDuv69vRaGnp6BJk4a0b+9E3bpWJCYmYWHR8h10vimOb/4Muo7LZHLaWLTCrc+nOLsMpXr1qtStW1OHbm0fhBBUqlQRVxdHGjXuQO06lpQtW5ohn7hjbGxIP3dnNqzZoftzaX2Okuon3X68iZEjJ2Np5YB9t3507tSWTp21R3s/Wh36F+ftaywsW/Li+XOuX1ONsDdr0Zg6dWvh531ct8MfmQ+uRQi+mT2Zv1duVs+Wv6ZipQr0cuqGZUt7WjTqTJkyZWjbUXsA411j17pNC3Jycmjf3IEubZwYPfFTatY2xd6xC/fvP+RqxLWCSj7YzmvetY/+zXftrO8ms/qvTVqxA+jlMBg7mz4MdP+cz8cM1boV6n3sFBU7gP5OI3C1H8yoQRMZ/vkg2nZoo+2QxEdBujAoOQyAF0IIK2AdsFGX0LRp0zYPGjTokhDCSi4vi5mpsdboYFJiCjXzRkMVCgUVK1bg4cN0kpLy9wOqtsmabTMzH3Hy1Bl6OHZV7+varROVKldk3uxFgGoEKy1Fc0IjJTlVPfugUCioUKE86emZpCSncvZ0CA8fZvD8+QsC/E/RsnUzjbYvX75S3V/uZE9SUipmZvmjw6amxiQX+oxJSSnq0d7Xth4+zMiTN2L37rWMHj2N2Nh4rfi9fPkSLy9/GjWpj6mGHSNSC8UxOSlVLaNQKKhQsTzpeXZec+N6DE+fPadZs/wLKQdHWyLCI7l394GW/bvJdzE0yR8BMjSuwb1U3aP+b+Je2n1irsfSpn1rncfTUu5iZJo/KmNoXIO7qffe244ukpNSNWZxTEwNSU3VzgdT0wKxq1Ce9PQMXr3KIj1dFcPL4ZHExcZTv4Hmsw9CCA39pqZG6tGk1yQmpajzRKFQULFCBR4+zCApMUUzf8yMSE5Rtd28eRft2veiW/f+pD/M4Nat2DxdqfgfCcTU1IjwS1fIzc2lfoO6xZLjqXk6nj55xoF93hgaVlfnrso3Y/Xtb695U37ronTp0pQqpc/t23cAiItLoHLlipo637MmFJRX7y9wfiQlpqCnpyjghxEpyWkcPRrIs2fPefAgnfv3H9C5U7t37qNu9p2Ji0vg/v2HZGdnc+iQL+07WGJu3pz69etwNsyPBYtmo6en4MwlP6D4alHhfjIyrKHhv6mpMcmF62xS6nv1E6hGtAGePHnKrt2HMDSqVmJ1KCU5DeMC55WRiSGphWpCQRmVT+XISM9UH+/t3otDBW5RsbQ2p2XrZpwNP8JB363Uq18HRUXN2b2PSXJyKiZmBWqRiZG6LwvKaMSvgip+baxaM+/HGVy6EsAX40fw1fRxfD52GLZdO3LnTiIPHqSTnZ2Nl+dRDI1rFIpdDdIK1bzU5DSMTfJjVz4vdm79e3Eq4AzZ2dk8uP+Q0PPhtDJvjmU7c7r37EpQmA8r1i2io401nwxzL5E+2nt4kyouBWZiTUyNtOq4KvcK2KpYjvSHGVhatWb+TzMJv3qCcRNGMvXrcYweq1pI47WO+/cf4u3pT5VqlYs9doD6++zB/Ycc8Q6gdZsW/F9DesZAoiCRgPYQw5tJBPbn/f8g0KoIuRCgIVBXqVQycKAbnl6aD496eh1l+HDVQ5z9+jlzIvC0ev/AgW7o6+tTp05NGjSoy4WQMKpVq0LFihUAKFWqFN3sbbh+PQZQPbTYqHF9nj17jlktE5RKJW79enHE94SGzSO+Jxj4iWqVHBc3R4JPnQcg8PhpmjVvrL5vuH0na25cv0WZsmWokffgrEKhoJtDF27djCU0NIIGDepSu3ZNlEolAwa44u2t+RCut/cxhg5VTR26uztx8uQZACpWrMCBA5uYO/c3zp4NVcuXLVsGI6Maals9e9px5nQo9evXoXZtM5RKJe79XfDx0RxR8fE5zpCh7gD06duLUyfPAlC7thkKhepHUc2aJjRsWJc78Ynqdv0HuLJvr/ZtRACR4dHUqmeGSS1j9JR69OjTjcCjwTplC1PDuDoGpVQjguUrlsfcuiVxt7QvfgCuhEVRu15NTGuZoFTq4dTXkRNHgt7JztsIu3SFuvXrUCsvdn3cnfHzCdCQ8fMJYNCQvgC49ulB8KlzAFStWlm9+lTtOmbUq1+HO3EJGm1zc3M19A8c6IaXl2YOeHn55+e4uzOBeTnu5eWvleMhIeEAVK9eFVD1WZ8+vdi9W3Wf7uHDfhgaVqdu/dp0smmLUqnEoVfXf53jCoWCKnlT/Hp6ejj0sCUw8CwNGtSlTp38/Nbl27Bh/QFVfgcGnnljfwQEBFOhQgUsLFqgVCpxcXHk3LlLGjLvWxNCQsM1PmfhOhMSGo6enpJaNU3Vx/9es5lOnduqng8oXQq5XEarVs3euY/iE5Jp186C0qVLAWBn15no6Fv4+gZQq3Yb2rZywLK5PUIIBvX9vNhqke5+OkODBnXy/R/QW3cOqvsp37+iUCgU6luN9PT0cOrVjaCT50qsDkVcukrderWoWcsUpVIPN/de+Ptpxs7f9wQDBrsB4OzmyOmg8+pjMpkMFzdHDh/I/9G5bdNurJrb08G8B317fcrtmDhyMlMoKcIuXqFevfxa0befM36F4ufnE8DgT1S1qHefngTlxc+15xDatLSnTUt71qzewrI//mbD2u0kJiZjZW2uzsMuth0IOXuROvVqYZYXO9e+PTlWaGGJY36Bmo6D0wAAIABJREFU9Buseli+V28HzgZdAFS3ynWwUd0zX7pMaSysWhJzM5bff1pOx5aO2Fg48eWYbzgTFMKIwRNLpI8G9B7FpYtXqFegzrr3c9aaVfD1Oc7gIarcc+vTk6CTqjru3GMI5i3sMG9hx9+rNrN08d+sX7udMmVKU66caga4TJnS2HXrTOCx08Ueu9JlSlO2XBn1fhu7DuoZEomPj/Qegw8jAPhZJpONEUKsA5DJZNZAGSHEySLaHALsUc0U2AI3ipDLBiYBR65eDmTzlt1ERd1g/rzphF6MwMvLn42bdrFl83Kio4JJT89gyDDVUntRUTfYt8+TKxEnyM7JYfKU78jNzcXY2JCNG5ahUKhWI9m3zxNvn2MArFr5K4kJyeQKQdAFb549e86avzZzI/oWM2ZPIiIskqO+J9i5bT8r1izizCU/MtIzGPeZahWazMxHrFm5Bd+APQghOO5/iuNHT1GtelW27FyJvoE+CrmC4KDzbN24m5ycHKZOnYun51YUCgVbtuzh2rWbzJkzjUuXLuPtfYzNm3ezceNSrl49SXp6BsOHTwJg3LgR1K9fh1mzvmTWrC8BcHUdjkwmY9++9ejr66NQKDh58gzr127ndswdDhzajEIhZ/u2fURfu8ns778i7NIVfH2Os23LHtauX0xYRADp6Rl8NnIKAO07WDH16y/IyspG5Oby9dR5PHyQDkDp0qWws+vEV5O/09l5OTk5LJq9lFU7lyBXKPDY6cXt67GMnzmaqPBoTh4Nppl5E5Zs/IUKlcrTxaET42aMpr/tMOo2rMO0+ZNe3wPC1tU7uRV9u0g7C2b9zvrdy5Er5Bz4x5Nb12/z5TdjuRp+jRNHgmhh3pQVm3+jQsUK2Dna8OXMsbh2GQzAtsNrqdegNmXKluZEuCffT13I6RPn1Lq/nf4jew6sR65QsHP7fq5H3+Kb2ZMJD7vKEd8Admzbx6q1v3Mh7Cjp6ZmM/WwqAB06WfPN7MlkZ+eQm5vD9Knz1KNdc3+cQb/+LpTOe9jPP3Af6RmZbNm8m6hrN5g3dzoXL6lyfNOmXWze9CdRUcGkP8xg2PC8HL+myvGIiABysnOYMuV79f27u3etpWrVymRlZTN5yndkZKjsbt68m60bliOXy9mxbw3pDzPxPHjkX+d46TKl2XlgHXpKPRRyBUEnz7J+/Xbu3EnA03NbXn7v5tq1G8ydO42LF6/g7e2fl9/LiIw8xcOHGXz66SR1v16/fpry5cujr6/E1bUHLi7DiI6+ydq12zh58hBCQFxcPLNm/fSvagLAlK++x8f7HxRyubrOAEya+BnTv56AXC7j7BlVTfjjj1V4ex9j0sTPuXH9DI8ePWbZn+toa23xzn0UEhLGgQM+XDjvR3Z2NuHhkaxfv0Mrr1+9fMXO/etQKOTs2n7wo/TTurx+8vLcjkKhYLO6n77m0sXLeHn7s2nzLjZtXEZUZBAPH2Yw/NP8JV2vXz9DhQL95OwylPj4RLw8t6NUKlEo5AQEBLNxw07u3EkqkTqUk5PDnJk/s2PfGuQKBbt3HORGdAzTv51IRFgk/n6B7Np+gD///oXgUB8y0jOZMDp/FZr2Ha1ISU4j/k7+xUdxMGPer4SEXSYj4xHd+gxjwufD6VdoQY2iyMnJYdaMH9l7cANyhYJ/tu3jevQtZn03mfBLV/HzDWDH1r2qWhTuT0Z6JmNGTX2jzkuhl/H0OEJA0CGys7O5cvkaOzbtJTYmnq17VyNXyNn7zyFuXo9h6qwJXAmP5JjfSXZvP8jS1Qs5EeJJZsYjvhw9E4BtG3bx+4ofOXL6ADIZ7PvHg+go3Q/slmQf5eTkMHP6D+w7tBGFXMGObfuIjr7Ft99NISzsCn4+AWzfupe/1/1BaPgx0tMzGP2W2FWvUY1t/6wEVBe/+/Z4EngsmHnf/FKssatZ25Q1W1WrDir09Di834dTAW8eQPkv+F99j4HsbfdMSuhGJpOZAMtQzRy8AOKAr1D98G8ClAMeAJ8LIY7IZLJKwA6gFvAEGCeEiHiTDT190xLpnOplKr5dqJjIePm0ROzoK0rmmrdeOaO3CxUTL3KzSsTO/ZeZbxcqJjJflEw+VC1doUTspL8ouRU1snNz3i5UDMjfsDpWcVJSfQTw8IWu9SGKn1J6+m8XKibK65cuETuxNw6XiB3jej1LxA5AeWXJxC5LlMw5C/As6+2rZhUHFfXLlIgdgNgHESVTjN6REXX6ffTfaFvi9pe4z9KMwQcihEgGtN9uBTY69iGEyACcP+qHkpCQkJCQkJCQ+Ojk/o8OrEsXBhISEhISEhISEhLvwf/mZYH08LGEhISEhISEhISEBNKMgYSEhISEhISEhMR7kfs/OmcgzRhISEhISEhISEhISEgzBhISEhISEhISEhLvw3/1ArKPjXRh8H+YboZFvQOteLn8+E6J2AFQyhVvFyoGXmS/KhE7MY9L7mU/r3KyS8RO5VLlSsQOgLKElpUtqWVEy+mXKhE7ABkltNSrvkJZInaycksmvwGMylYuETs3I3a8XaiYKFNCy3uW1DKiKbf9SsQOwFirGW8XKgbCX6S+XaiYiHxaMt/ra8u1LRE7EiWHdGEgISEhISEhISEh8R78r77gTHrGQEJCQkJCQkJCQkJCmjGQkJCQkJCQkJCQeB+kVYkkJCQkJCQkJCQkJP5nkWYMJCQkJCQkJCQkJN6D/9VViaQZAwkJCQkJCQkJCQkJ6cLg/yesulqyPnAdm4I2MHDCAK3jLdq14C+fFfjEetHZqbPGsc+//Yw1x1az5thqbF27aLW169aZoBBvzlzyY9JXo7WO6+sr+XvjYs5c8sP72C7MapmojzVt3gjPo/8QePYwAacPYWCgr9F2886/OHHGQ/13d4cuXAw7RvjlAKZ+PU6HLX02bVlO+OUAAgIPUKuWKQCWlq0IPutF8FkvTp/zxsXVEQBTU2O8fHYQcvEo50P8GD9hJACODl25cjmQqMggpk+foNPO9m2riIoMIujUYWrXNgOgSpVKHDmymwf3o1m29CeNNp6HtxFy4Qhhl47x14qfkcvlH8UngCtRpzh7wZfgs14EBqni5+Bgy+XLJ4iMPFWkT9u2rSQy8hSnTnkU8mkX9+9fY+nSHzXaKJVKVq78lStXAomICMC5t8NHyQelUsnvy+YTHOpD0AUvnHs7qH0KCz/O5SuBfP31eJ0+bdn6F5evBBJ48hC1aql8srfvTPBpTy5c8CP4tCe2th3UbXz9dhEWfpyz53w4e86H6tWrfpTYDRzYm9DQo4SEHOHw4a1UqaK9DKZ9dxvOXfTjQrg/k6eO1RnL9ZuWcSHcnyMBe6mZlxs1a5mSkHaZE8EenAj24I+lP2joi44KZuaMiTr9+GfHaqKjgjkT7Kn2A+CbmZOIjgom8uopHB1sATAzM+HY0b1cuRxIRHgAX076XC0/d840btw6y+WrgTxIj+ZmzDmmFZHfW7auIOLKCU6cPKjObzv7zgSdPsz5C74EnT6s0UcDBrhy/oIv5877ctBjc4nErihs7TsRcP4wJ0O8GD/lM512/lr/GydDvDh0dAdmNVX5rqenx+KVCzgStJ/jZw8x4avPtdoWJPhCGK4jJuM0fBLrdx7UOp6cdo/R0+fjPnoao6bNJfXeA/WxJWu20eezr+g9agq//LUBIVSjlTKDcigNGxVbPgCsW7uY5MQIwsOOa+iaO2caV6KDCAk/RtK9K1y9Hvxe/fIaUzNj4pLDmPhlfqzHTRxJ8Hlvgs55sXbjEkD2xlgW5vufl9DFeTB9hmnn5/vSwtacn48v59fAv3Aa31fruOPnrizwX8aPvkuYsWMeVU2rq49tiNnDDz5/8IPPH0xeN+uNdjrateNg8E48zu5m1KRhWsfbtG/NP0c3EpJ4ku4uXdX7jc0M2XFkA7uObWbfye30/7SPls6oqGBmTNedDzu2ryIqKpjgIM18mDljIlFRwVy9chKHAvkwefJowsOOE3bpGNu2/oWBgQEAdnad6HZ0Ad39f6arx1zK1jHE0K4VPYJ+p+eZxTSe5Fqk76bObemfsoPKresC/4+9846K4nof9zO7FEUFO12xFyzYe+8idk1iT6IxzV5i7BpbEnvvvXelSlFUFBVQsCBgAQQWULpddpnfH4sLyy6x/ITk+znzeDjHnXnvfee9951753Yo37YOnc4tosv5ZXQ6t4hyrWr/Y9r9F8gqhL9/A6lh8JkIgmAhCMJhQRAeCYIQKgiCmyAI1QVB8BAEIU0QBJc88pcFQQjO/lMIgnD6U/TJZDJ+WfQLs0fMYUzHsXTo054K1SpoyTyLe8qKySu4cPqC1vWmHZtQtU4Vfur2C+OdJjLwxwGYFDfRinvJ8tkMHTiWds2c6DuwJ9VrVNGK45vhA0hPy6Blw+5s3biH2fOnACCXy1m/9U9+m7yA9i16M6DXSDIzc/Yj7+nUmZcvXmnpWrFyAQP6fUuTRt0YOMiJGjWraukaMXIwaWkZONTryIb1O1nwx28AhIZG0K51H1q36EX/vqNYs24RcrkcpUrJrJlLaNKoK506DGDMD8OpXbsGa9YsonefEdR36MhXg/tQs2Y1LT3fjvqatLQ0atu3Ye267SxeNBOAN2/esmDBcmbMWKSTD0OG/kSTpt1o0LAzZcuWoV//ngVi03scewyhdYtetG/TB5lMxpo1i+jTZyQODp0YPLi3jk2jRn1FWlo69vZtWbduO4sW/Z7LphXMmLFYx6YZM8bx7FkSdeu2x8GhE9evBhWIP0yYOpakZym0btyTts2c8PcLQCaTsXLVQvr1HUWjhl0YNKg3NfOk3chRg0lLS6de3fasX7eDPxapK9vk5FQGDvyepk2788OYKWzfsUor3HffTaRF8560aN6T5OTUL552crmc5cvn063bVzRp0o07d8IYPVa7cpfJZPy5Yh5fDRhDqyY96T+wl05aDh0xiLS0dJo6dGHzht3MW5Czp3pU5BM6tO5Dh9Z9mDppnlZ8det34Kuv+lKrlrYd3337Damp6dSs3ZrVa7exdMksAGrVqsbgwX2o59ARx15DWbdW3bBVKpVMm76AuvXa06q1Ez/9NEorzg3rdwHQqEEXatds8495VL9uBzZo5VEKgwaOplnTHowdM5VtO1Zq0u6vv+fSs8cQmjfrwd1CSLv8kMlk/PHXTEYO/onOLfvSu38PqtWorCXz1bD+pKdl0K5JL3Zs2seMeRMBcOzTFSMjQ7q1GYBjx68ZMnKgptGQF5VKxeK129m4dBZndq7C/bwfj6JitGSWb96DU5f2nNy+kh+HD2LNdvU5CMH3wrh1L4wT21ZwavtK7oY9IjDkHgAGpazITIr8Yv4AsHfvURx7DdVrx5aNu0GAlk160qBOh0/OF4BFS2fi43VJ89vC0pwxY4fTuV1/2jTvhUwmQzAupld/fvTt2YXNK3XL7E9FkMkYvnAMq0YtZlaXiTTr3RqrqjZaMk9CI1noNJ25PSYT6H6Nwb8P19x79+Yd83pOZV7PqawdsyxfPTKZjBlLp/DrkCkMaDuU7v06U7m6nZZMfFwi8yYsxuOUl9b1Z4nJjHL6ka87j2J4jzF8O24Y5czLasVZv34HvvqqD7Xy1nvffk1qWjq1a7dm7dptLFmsrvdq1VT7g4NDR3o5DWPt2sXIZDKsrCz45ZfvaN7CkQYNOyOXyxk8uDcA69ct5cYvG/HuMpMnJ69Sa1JfGiwZhd/QvzjXbjq2fVtQorp2oxDAoFgRqo7uRnLQw5x0S3nOlRHL8eo4g4Dxm2m6TreTSKJwkBoGn4EgCAJwCvAVRbGKKIq1gZmAOfA3MDxvGFEU24ii6CCKogPgD5z8FJ01HKqjiFKQ8CQBZaYS37MXadG1uZZMYuxTIsOiyBK1571VqFaB29fvkKXK4u3rtzwOjaRx+0aa+w0a1SXq8ROeRMeSmZnJmRPudOvZUSuO7j07cvSQui3jcsaTNu3Uutt1bMX9uxGE3g0HIDU1nawsdTvXpJgJY38eyZrlWzTxNG5cn8ePo4mKiiEzM5MTx11w7NVFS5djr84cOnACgNOn3GnfviUAr1+/QaVSAVDE2Jj3ZiYmPCMkWF1JvnjxkvDwh3To0IpHj6KIjHxCZmYmR4+dxSlXbzyAk1NX9u0/DsDJk6506NAKgFevXnP1agBv3r7VyYfnz9UHZRkYGGBkZIgoigVikz6aNHHQsunYMWe9Nu3X2OSmY9Pbt2904h05cjB//bUBAFEUqVjJtkD84euh/Vi7aptGT0pKGo0bO/D4UU7aHT/uTK9e2jb1cuzKgf3qtDt1yk2TdiEh90iIfwqoG1jGxsYYGWmPVhVk2gmCgCAIFCumbmSbmhbXPM97GjauR+TjaKKz7Tt1wpUejp21ZHo4duJwdu/x2dMetGnfgvzIG9/Ro2fo7dRNS6a3U1f27TsGwIkTrnTs0Dr7ejeOHj3Du3fviIqK4dGjKJo2aUBCwlNuBd8F1O9PWNgDrK0sNPHZ2Frp5JGOfzt2yZVHOf59OyRUbx69TzsTk8JLu/xwaFiHqMgnxETHkZmpxPmUB116dNCS6dKjPScOnwXA7awXrdo2A9R+bGJiglwup0gRYzLfZWrKiLzcCXtIBWsLbK3MMTQ0pEeHVly4GqAl8zg6lmYN6wLQ1KFOrvsCb99lkqlU8i5TiVKlpEypkghGJojKd6DK/GL+AHDZ7zopqWl67bC2sfz/ypcejp2JjoohPOyhVhgDAwOKFC2CXC7HxKQoZKn06s+Pxg51MTMt8Ulh9FHZoSpPoxN4FpOIKlPJDWc/GnRtoiUT5n+Xd2/Uh2g+uhVBKYsyn6ynToNaxETGEvdEgTJTybnTPrTv1kZLJj4mgQf3H5GVpV0xKDOVZL7LBMDI2BD1J4l2nO/9QW+9994fTrrSIdsfnJy66vhDkyYOABjIDSianTdFTYoSH58IqP3fsHhRAAxN1e/yi6hEXj55hpipIubMNay6NSIv9r8NJGKDC1lvcw4iTbsbzZtEtc9lhMciMzZEZvTfXgYrimKB//0bSA2Dz6MDkCmK4ub3F0RRDBZF8bIoij7A8/wCCoJQAugIfNKIQRmLsjxTPNP8TopPouxHFkaP70fSpH1jjIsYY1rKlPot6lHOKmfo08LSnLi4nBMZ4xUJWFiW14rDwtIcRbaMSqUiI+M5pUuXpErVioiIHDqxFc+Lx/l5fM7Q8G+zxrF5w25evX6tuWZpZUFsbM5pwYq4eKwszbV0WVqZa2Q0usqopxk0blyf6wEe+N9wZ+L42ZqP6vdUqGBNvfr2pKamEROr0FyPi4vX+tgBsLKyIDZb5r2eMmU+fCKqi/N+YmNu8fzFS06fci8wm0RR5PTZPVz0O8Oob7/Wet73NllZaev5VJvMzEwBmDdvKv7+rhw4sInqNat+cX8wNVNX2L/NGofnxeNs3b2KsuXKYGVlTmyctk2WOjblyORnU9++Pbgdco9373Iqmi2b/8b/mhu/zRhXIGmnVCoZP34WgYGeREYGUqtWNfbvPaYlY2lpjiI2Jy0VigQd+ywtzYnL6xvZ02oqVLTh/OXTnHXbT/MWjXXii42LxyqvX1tbaHxfpVKRnp5BmTKlsLKy0HonYuPisbLWDluxog0O9etw/cYtzbWBA3vRsFE9Nm7+k5IlTYmLS9DVaWVObFyODekfyCOlUsnECXO4HuDOw8fXqVmz4NMuPywszYmPS9T8jlck6vd3RaJGz/OMF5QqXRK3s168evWKgFAf/EM82bphD+lpGXr1PE1KwaJcWc1v83JlSExK0ZKpXsUO70vXAPDxu87LV69JS3+Og30NmjrY03HQGDoOHkOrxg5UrmgDcgNEVaYm/Jf2B330HeBIgwZ1WbNhCWYlTT8pX0xMijJ+0hj+XrZeSz4hPpEN63YQfM+Xew+ukJHxHDHzNf8GpcxLk6JI0vxOiU+hlHn+dW3bwZ2443tT89vQ2Ii5Z/9k9qmlNOia/6nA5S3LkajIaQwnxj+lnGW5fOXzYm5VniPn9+AedIrdGw7wLDFJJ864uASsrC21wlnnqq/U72q2P1hbatVjcbEJWFtZolAksGr1Fh49vM6T6JtkpD/H21s92jP2x2m02j+NnkHrqDiwNU8v3+N1XM70t9fxKRS10C4HStapSFGrMsR73yI/rB2bknY3mqx3hXcaukQOUsPg86gDBH1m2H6AjyiKemsPQRB+EAQhUBCEwNgXMbmu68p+bGPy5qWbBFwIZNXpFfy+/jfu3wxDpcz5oBb0RJ43ar0yoohcbkDT5g35Zcx0+nQfRo9enWndtjn2dWtiV7kC7i4+eeLRZ4e2NkHf3NJsmcDAEJo16U77tn2ZMvUnrfUMxYqZsO/gRmZM/4M3b3R7+3X0fMSz6KOX0zAq2jXG2MiIdu1bFphNXTsNom2r3gzo9x1jxg7XmSKg3yb9+ZQfBgZybGys8PcPpEULR65fD2LQ171148jz+1P9wUAux9rGkoDrt+jabiBBAcHMWzTt4573AzK1alXjj0UzGDdupubad99NoGnT7nTpPIhWLZvQtm3zf4zjn2zKDwMDA374YTjNm/ekUqXG3Llzn4lTxn5ynPrfP5HEhKc42LenY5u+zJm5lC07VlDUpMhn2vHhZylWzISjR7Yxeeo8Ta/35i17mTJ5Hs5nz5GY8Iwly2Z9gk7tPFq46DfGj1OHNzAwYPSYobRq0YuqlZtx925Ygadd8RL5TE35mPc3HxmHhnXIUmXR1L4zrRv2YMwvI7GtqDt14v1z6ajOE/HUsSMIvH2PQWOnEhgSSvmypZHLZTyJi+fxkzi8j2zB58gWrt+6S+DtUP16vpA/6GPzlr3MmLoQVxcvEhOesXDxjI/XichvM8ezecNuXr58pXXPrKQpPXp2olHdjtSp3hoTExME4+L/+CwFxiekS4u+bbGrVwX3rTlr6Ka2HMvC3r+xZfxqhsz9lnIVzPWG/f+q1IFExVO+6jiSPi2+wmlwD0qXLfVRz55fvufn4yVLmuHUqyvVa7Sgol0jihUrypBv+gMwYfwYrgz7G7dG44g6fJGKg9voiyS3cuovGMbt+Qfytcu0ujV1Z3/Nzek78pX5r5CFWOB/H0IQhO6CIIQLgvBQEASdRS2CIEzOnu5+WxAEH0EQKn4oTqlhUPh8AxzK76YoiltFUWwsimJjm+K2mutJ8UlavfxlLcuSnJisLwq9HFp3mJ+7/8rvQ2chCBAXmdNTFK9IwDpXT5GllQWJeYb14xUJmt4kuVyOqWkJUlPTiVck4H8lgJSUNF6/fsN5r0vUrV+bRk3qU6++PTdue3HGfT+Vq9pxwmU3irgEbGxyejCsrC2JT9DWpVDkyLzXlZKiPawdEf6Ily9fUbt2DUD9obH/4EaOHjmL89lzxMXFY2uTM9fX2toSRXyiVhxxcQnYZMvkpyc/3r59i4urF46OnQvMpoTsOJKeJeNy1pOyZUtrnve9TfF58ikuLv6TbEpOTuXly1ecOeMBqKdUWVlbfnF/SElJ49XLV7g5ewPgfPocdevVVueBtbZNeaeUKHLJ5LXJytqCQ4e3MGb0ZCIjn+R6PnVev3jxkqNHz2JuXu6Lp139+urFcY8fRwNw4oQLTZo11H52RQJWNjlpaWVloWufIgHrPL6RmpLGu3eZpGbrDwm+R1TkE+RyuVZ8NtaWmmF9jR2xOb4vl8sxMzMlJSVV552wsbbUpJOBgQHHjmzj0KFTnD7trpF5+jSJ2BgF1taW7Np5iMaN6mNtbaGrMy4BG+scG8zy5NHBw1v4YfQUTR7Vy067979PnnAt8LSrWrUS+khQJGJpnfPxZmllTmLCMy2ZeEWiZoRJLpdTwrQ4aanp9BnYE9/zV1AqlSQnpRB0/Rb1HOz16jEvW4aEZzk90YnPkimfZ1SlfNnSrF4wnWNbljP++28AKFG8GD5+N6hXqxomRYtiUrQorZs24HZoBKiUCHJDTfgv5Q/58fRpknq0zdqCfXuO0rBRvU/Kl4aN6zNv4TRu3jnP2J9GMnHqj3z/wzDatW9JdHQsycmpKJVKXJw9EQyM//FZCorUhGRKW+WM7JS2LE3a0xQdudqt6tHr1wGsGb0UZa6e7bSnqQA8i0kk7No9Ktrr97uniqeYW+WMTJlbludZQpJe2X/iWWISj8Ijadi8vk6c1tYWxCsStORj4+K16iIzU1NSUtKIi43XqsesbSxQxCfQqWNroqJiSEpKQalUcvq0O81bNKJs2dLUrVeLlFuPAIg5e43iFc0pap0zulLUsjSvE3PKUIPiRTCtaUu7k7PpcWM1pRtWpeXuKZoFyEUtS9Ni5yQCxm/mZbS2T0noIgiCHNgA9ABqA98IgpB31fYtoLEoivWA48BfH4pXahh8HvcA3YlzH0AQhDJAU8D1U8OGh0RgbWeFua05BoYGtO/djmte1z4qrEwmo0RJ9VSOSjXtqFSrEkGXcgY8gm/epVKVithWtMbQ0JA+A3pwzl17AfM59wsM/ka980GvPl3xu3QdAF+fK9S2r6GZf9i8VRMiwh+yd+cRGtRqT9N6XejTYxiPH0YxoNcogoJuU7mKHRUr2mBoaMiAgb1wc/XW0uXm6sM3QwcA0LdfDy5e9AfU0xzeL8y1tbWiWvXKRD+JBWDDpmWEhz9iwzp1L0NgYAhVq9phZ2eLoaEhgwf1xsVFewGXi4sXw4cNBKB/f0d8fa/8YzoWK2aChYW60JXL5XTv1pGIiEcFYpOJSVGKF1f3cJqYFKVjp9acO+dL1aqVNDYNGuSk16ZhGpt64ut79R9tAnB19dbsFtOhQyvuhIR+cX8A8PTwpWUb9dB663bNiQh/RFBQCFWq5qTdwIFOuLpq2+Tq5sXQYeq069evJxcvqm0yMzPl5IldzJv7F9eu5fizXC7XTGMxMDCge4+O+Pr6f/G0UygSqVmzGmXLlgagU6c2PAh/pCVc2ZEYAAAgAElEQVRzK+gOlSvbUSHbvn4DHPFw0x5F83A7z9ffqHc+6d23O5ezfaNMmVKaxaAV7WypXMUOTw9frfgGD+6Ds4unVnzOLp4MH67etWzAAEcuZPu1s4sngwf3wcjICDs7W6pWrcSNAPVw/ratK7gf9pDVa7ZqxWVhUZ6goNtUqWrHiJFfcf/+AwYOdNL1bzfvXHmU499mZiU4cWIn8/PkkUKRQM1aOWnXsVPrAk+7qDwLfd8TcuselSpXxLaCNYaGBjj1646Xu6+WjLeHLwOyR9J69u7C1cs3APVH93ufLmpSlAaN6/HoQaRePXVqViU6Lp7Y+EQyMzNxv3CF9i21566npmdo1uRsP3iKft3Va3ssy5cl8HYoSpWKTKWSoNv3qFzBBvHdK/UHtNzwi/pDflhYlNfky7ARAwkPe/hJ+eLUfQgN63akYd2ObNm0h9XLN7Nj635iYxU0buJA0aLqEbG27VpArilShUlkyEPK21lS1qY8ckMDmjq15pZXoJZMBftKjFwylrWjl/E8OWfw38S0GAbZ8+KLlypBtUY1UTyI1avnXnAYFSrbYFXBEgNDA7r17YSvp99HPWN5y3IYF1GPLJcwK4FDk7pEPXyiFed7f9Bb7733h1z1nouLl44/BAQE8yRGQbNmDTR506FDa8LCHpKamo6ZqSnFK6sb7+Zt65B6N5LilSwwsS2HYCjHtk9z4s/lvPfK569xtv8R96YTcW86kZSbD7k6agWpIZEYmprQat9U7i49QnJAxEelw7/Nf2BXoqbAQ1EUH4ui+A44DPTJLSCK4gVRFN8P0V0DbPgA/+2VHf9dzgNLBEEYI4riNgBBEJoAJqIoXvyHcIMAF1EUdVeAfoAsVRYb5mxiyf5FyORyPI94Eh3xhBFThhNxO4JrXtepXr86c7fNoYRZcZp3bsaIycP4ofOPyA3lrDixHIBXL17x5/i/yVLluJxKpWLmtMUcOrENuVzG4f2niAh7yLSZvxJy6x6e7hc4tO8E67b8ydWbHqSlpvHjd1MBSE/PYMuGPbifP4ooivh4XcLH85JeG97rmjZlPqfO7EEul7Fv7zHC7j9g1uyJ3Lx5B3c3H/buOcLW7SsJvn2e1NR0vh05HoAWLRszafKPZCqVZGVlMXniXFKSU2neojHfDOnP3bth+PmrN4OaM2cZEyfOwcV5P3K5nN17jnD/fgRz507hZtBtXFy92LX7MLt2rib03mVSUtIYPiJna7fw8KuYliiBkZEhTk7dcOw1lJSUVE4c34mxsRFyuQxf36vs2H6wQGyys7PlwGH1EhYDuZxjR89y7twFJk6cg7PzPuRyOXs0Nk0mKOgOrq5e7N59hJ07V3Pv3iVSUtIYMeLXXDZdoUQum3r1GkZY2ANmz17Kzp2r+fvveSQlpTBt3Fxq1Kr2xf1h8fyVrNuyjIVLZ5CclMqkX2ahUqmYMnkuZ87uRS6Xs3fvUe7ff8DsOZO4efMObq7e7Nl9lO07VnL7ji+pqWmMHDEOgLE/jqBylYrM+H08M35Xp2dvp+HqEZCzezE0MEAml+N74Qrbt+8nOjrmi6fd4sWr8fY+RmamkidP4pj4S850pvf+PmPaQo6d2oFMLufgvuOEhz1kxqzxBN+8i4f7eQ7sPcbGrX9zI9iLtNR0xnw7Se0brZowY9YElEoVWSoVUyfOJTkpRRMfgsDuPUcIDY1g/rypBAaF4OLixc5dh9mzey1hoX6kpqYxZJh6a9bQ0AiOH3fmTsgFlCoV4yfMIisri1YtmzB82EBu3wklMMBT8/64e5xn2dLZNKhvjyAI/DruO5KTU9m967CePDrC9h2rCLlzgdTUdEZp8mgklatU5Lffx/Hb7+prfZxGkBD/lKVL1nDO84g67WLimPDz7wWadmmp6fmWSXN/W8LeY5uQy+UcPXiaB+GPmDzjZ24Hh+Lt4cuR/adYtWkJFwNcSEtL59fR0wHYu+Mwy9f9gdeVkwiCwLGDZwgLfaBXj4Fczsxxo/nxt0WosrLo16MjVe1sWb/rMPY1qtChZRMCgu+xZscBBAQa1avNrPHqrYK7tG3O9Vt36T96MgICrZo40L6let2EMk2BYdlK3L3t+0X8AWD/vg20a9uCsmVLE/U4kAULl7Nr92GWLZ1NQ4c6CAL8+Mu3JCensm/3kY/Ol/y4GXgb5zPnOH/5NEqlkju375P1Rv9ajfyYNm8ZAbduk5aWQae+w/j5++EMyLMQ+2PIUmVxYO52puydg0wu4/LR8ygexNB30tdE3XlIsHcgg38fgbFJEX7eqN6NLTkuibVjlmFV1YaRS8aSJYrIBAHXTadQPNTfMFCpVPw5cxUbD61EJpdz5pALj8Mj+Wn6aEKDw7jo6Udth5qs3LkU05IlaNulFT9OG83AdsOoVM2OyfN/fT8njL2bDvEw7DGAJk6lkMWe3UcIvR/BvLlTCbqp9odduw6ze9caQkP9SE1JY9jwbH+4r/aHkJDzqJQqJkyYTVZWFgEBtzh50o0b1z1QKpUEB99j+/YDqFQqfvppOtu3z0PMyiIz/SWBk7ZSoqoVbQ79hiCXEXX4IhkRcdSeNoDUkEjiPW/qTQuAKt91pXglc2pN7EetiepG5eWvl/E2+dP84H8NQRB+AHLvCbxVFMX3PTjWQO4ej1ig2T9E9z3g/g/31Tr/rVXP/9cRBMEKWI165OANEAVMBHYCNYHiQDLwvSiK57LD+ALLRFH0+Bgd3Wx7FErm3H4eXRhqAHiZ+cltos/ibSH1NhnnGsYvaN6pCmchVqkihTe3N+Pdqw8LfQFUWYWzI3RxI901AAVF2puXhaKniIH+nZ6+vJ7Ce5eKGRZOPj0IyX8u9ZfGpHL3QtFTssinbSP6ucQ//qhq8ovwQ+NpHxb6AgS/Sfiw0BfiXmrh1OsHS7f7sNAXYmD8gU873KKA6VXBscC/0VyeuOZrsyAIg4BuoiiOzv49HGgqiuI4PbLDgF+BdqIo6i7CzIU0YvCZiKKoAAbruaVn9Y0mTPsCeyAJCQkJCQkJCYlC4WMWBxcwsYBtrt82gCKvkCAInYFZfESjAKQ1BhISEhISEhISEhL/1wgAqgmCUEkQBCPga+BsbgFBEBoAW4Deoih+1IpuacRAQkJCQkJCQkJC4hP4t6fii6KoFAThV+AcIAd2iqJ4TxCEhUCgKIpnUR+6Wxw4lr1V7RNRFHX3JM+F1DCQkJCQkJCQkJCQ+D+GKIpugFuea3Nz/b+zTqAPIDUMJCQkJCQkJCQkJD6BwtnSovCR1hhISEhISEhISEhISEgjBv9lfJ/dLRQ9JoV4wqS5SakPC30BBharUSh6glS6J2IWFImZhbOfc8zLZx8W+kLIhcLpmyhfzKxQ9LxWvSsUPYVJYW0jmlWI83ULazvjUa3mfljoCyGXFc67VMKwaKHoKawtRAG2Bv5dKHpq1xpUKHoKk3olk//tR/jXEP/9XYkKBGnEQEJCQkJCQkJCQkJCGjGQkJCQkJCQkJCQ+BT+A+cYFAjSiIGEhISEhISEhISEhDRiICEhISEhISEhIfEp/NvnGBQU0oiBhISEhISEhISEhIQ0YiAhISEhISEhISHxKUhrDCQkJCQkJCQkJCQk/meRGgb/cbp2ac+d276E3rvM1Kk/69w3MjJi/76NhN67zOVLZ6lY0QaA0qVLcu7cEZKTwli96g+tMM5n9xFw4xy3bnqzft0SZDIZnTq35cZNT4JCfJg4eaxePTv2rCEoxAevC8exrWCtdd/GxpKYhBB+Hf+95tq6jUuJiLzO1Rtap3XTpmMLzvmfwPvGaX4YP0qPLkNWb1uK943THPfYg7WtJQCGhgYsWzsPl4tHOHvhEE1bNtKE2X96C+f8T3D2wkHOXjhIsTKmWnFWb1ePyT7Lmeq7knY/OenobDq0ExM8ljHObQljj82jfFW1fSYlizP60Czm39tJ7wW6z6qPxu0bscN3O7su7+Srnwfr3K/brA4b3NbjHulKm56tte6Nnvk9W723sP38Vn5e8NM/6mnZoRln/A7h7H+U734drnO/YXMHDnvuIij2Ep17ddBcr2Ffjb0uWzl5cT/Hzu+lW59OOmE7dW7D9ZvnCAz2ZsLkH3TuGxkZsWP3agKDvfE6r+sP1jaWPIkP1vKH4LsX8LvmwsUrZ/G5eFJzvXOXtgTd8ib49nkmTflRr65de9YSfPs8531PUiFbV6NG9fDzd8HP34Ur11zp5dQVAGNjIy5cPMWVa65cD/Bg5qyJALTt2BKf62e4EODMjxO+06PHkHXb/+JCgDOnPPdjbWsFgIGBAcs3/IH75eN4+Z/ip4nqsJZW5hw8vR0v/1Ocu3KSUT8MAaBDp9b4Bbjhf9ODXyeO1qtny86V+N/0wM37MLYV1HpsK1gRGX8L78sn8b58kj9XztOE6dOvB+evnOaivzPbdq/CL8CNsFA/pk/7RW96HTywibBQP676OWvKBIDfpv9KWKgf9+5eomuXdtnpZYz/FReCAr0ICT7PvLlTNPJbtyzH98pZLl49y869aylWzISOndtwLciDG8FejJ+kzzcM2b5rNTeCvTh3/pjGN2wrWBOTeJsLfme44HeG5asW6ISFgvE9U7MS7N63jmtBHlwL9KBRE4fPzieAWvbVcfE8xEV/Zy5cOYOxsRFFixZh/5HNXL7hykV/Z2bNm6wTZ712DVh+fj0rL27E6af+Ovd7ju7NX95rWeaxipkHF1DWuhwAZa3LsdhlOUvcVvKX1xo6De2mN+0Kq7740u/Se2QyGS4XjrD94Dq99tVp58ASn7Us811Pz5/66dr/vROLvFaz0H0l0w7Mo0x2+gHseHSUBW7LWeC2nPHbZuiN/2OYvWQlbR2/pu8w3bLqYyiM+q90Wd3zgrp2bc/dOxcJDfVj2lT95caB/RsJDfXD77Kzlm94njtKSnI4q1cv+qB9Jq0bYee2HTuPnZQarVv/mfbtQuUrh6lwcgMVTm7AdGB3zb1qd1011602zP+grn8bsRD+/RtIU4k+E0EQLIDVQBPgLRAFTATWAs0BP1EUe+WS7wT8jbox9gIYJYriw3/SIZPJWLNmET0dhxAbG8/VKy64uHgRFvZAI/PtqK9JS0ujtn0bBg3qzeJFMxk2/GfevHnLggXLsa9dA3t77cO+hgz9iefPXwBw+NAW+g3oyaw5k+nXeySKuATOXzqJu5sP4WE5jzd85CDS09JpVL8T/Qc6Mv+P6Xw/coLm/uI/Z+HtdUlLz6EDJ9m2ZT+bt+UcHiOTyZi/bAajBv1MgiKRE577OO9xkYcRkRqZgUP7kpGWQeemfXHs25Vpc8czcczvDB6urgh6tfuK0mVLsePwOvp3Ga5ZADTlx9ncDbmvjiPXAWeCTKD3wm/ZMWwpGQnJ/HJ2Efe9bvL0YZxGJuTMVW4c8AGgVueGOM4Zxq6Rf5L5NhOvFccxr2GDRXXbf8oujX2/LvqFGUNmkhSfxDqXtfh7XePJgycamadxz1g+eQUDxw7QClu7US3sG9fmx67qBsHKkyuo17wet6/d1qtn5tKpjB08gcT4pxz02IGv52UeR0RpZBLiEpgzYREjfx6iFfbN6zfMHreQJ5GxlDMvyyHPnVy9cJ3nGS80cf+1Yj79+4xCEZeAz8UTeLieJzw8xx+GjRhIWloGjR0603+AI/MXTuP7URM195csm4VPHn8A6O04nJTkVC07VqxcQB+nEcTFJeB7+TRurt5avjdi5GDS0jJwqNeRAQN7seCP3/h25HhCQyNo17oPKpUKc4tyXL3mirubD2/fvqNXz6G8fPkKAwMDPL2PEnA5gIV/zWT4gLEkKBI5430Qbw9fHoY/1ugZPKwf6WkZdGjiRK9+3ZkxbyLjRk+nZ58uGBkZ0aPNQIoULYLX1ZOcPeHBu3fvWDx3Ofduh1GsuAnOPoe54HuFpcvnMLjv98QrEvG4cBRP9wtEhD/S6BkyfCBpaem0aNidPv17Mnv+VMZ+p/6IjI6MoXMb7Q/GUqVKMmfhVLq1H0hqajoR0TeYPnkBuw4e5Zq/G84unty/n1MmfPftN6SmplOzdmsGD+7N0iWzGDL0J2rVqsbgwX2o59ARKytzzrkfppZ9G96+fUvnroM16XXJ9xQeHhe4fuMmU6bOR56pfr/+WPI7o8cOZ9jIQQzs8y2KuAS8fE/g4eajZd/QEYNIS0unqUMX+g1wZN6CaYz+Vu0bUZFP6NC6j45f5PaHgvC9pX/Nxsf7EqOGj8PQ0JBSZqZ4nD/6Wfkkl8vZsPUvfh37G6F3wylVqiSZmUqMjY3YtH4nVy7fwNDQkGNndvKqfQIhvjcBEGQyvv3jB5YOnU9yQjKLzv7FTe8bxD2I1eiMuveY2b2m8u7NOzoP68Y3v49g3a8rSH2ayrz+M1C+U2JsUoS/PNcQ5HWDtKfa71Jh1BeOfbsxZeYvX/RdiotRqJ9v7FAeRjymeIniOr4hyGQMXziG5cMWkpKQzNyzfxLsFYDiYU76PQmNZKHTdN69eUeHYd0Y/PtwNv26EoB3b94xr+fUfH3vY+nbswtDBvRm5h/LPzlsYdV/+vSuWbOInj3VvuF/1RUXF0/u5/aNb78mNS2d2rVbM3hQb5YsnsnQYWrfmL/gb+zta2BvX/NDBlJ+zi/EfT+TzMQkKh5dy8sL13j36ImW2Av3SzxdtFEnuPjmHU/66zZaJAoXacTgMxAEQQBOAb6iKFYRRbE2MBMwR/3xr9t9C5uAoaIoOgAHgdkf0tOkiQOPHkURGfmEzMxMjh47i1N2r+h7nJy6sm//cQBOnnSlQ4dWALx69ZqrVwN48/atTrzvC3kDAwOMjAypVKkCjx9HEx0VQ2ZmJiePu9LTsbNWmB6OnTl04BQAZ0550K59C829nr06Ex0ZQ1iujxOAq1cCSE1N07pWr6E90VExxETHkZmpxPW0J516tNeS6dyjHSePuADg4exDizZNAahaozJXL90AICUplYz059R1qP2BVARbh6okRyeSGvMUVaaKEGd/anVtpCXz9sVrzf+NTIw1hW3m67dEB4ajfPtxJ6XWcKiBIiqehCcJKDOVXDx7kZZdW2jJJMYmEhkWqbOjgSiCkbERBkYGGBoZYmAoJzUpFX3UaVCbmMhY4p4oUGYq8TjtTftubbRkFDEJPLj/iKysLK3r0Y9jeBKprkyfJSaRkpRKqTIlNfcbNa5HZG5/OOFKj17aowo9HTtz+KC61//MaQ/a5vGHqChdf9BH48b1efw4mqhsXSeOu+DYq4uWjGOvzhw6cAKA06fcad++JQCvX79BpVIBUMTYmNzJ+fLlK0Ddy2ZgaEC16lWIjszxO+dTHnTJ43ddenTgxOGzALif9aJlW7XfiaKIiUlR5HI5RYoYk/lOyYvnL3iWmMS922FqfS9e8fDBY1q1bU7k4yc8iY4lMzOT0yfc6Nazo5aebj07cvTQGQBczpyjdbvm/5hGFe1sePwomuTkVBo0qkfMkziaNmugLhOOnqG3k3bvcW+nruzbdwyAEydc6dihdfb1bhw9eoZ3794RFRXDo0dRNG3SQE96GWp8831ZAVCkiDFW1hZavnHqhCs9dMqKThw+pC4rzp72oE17bf//JwrC90qUKE7Llk3Yt0edJpmZmVSpWumz86l9x1aE3g0n9G44AKmpaWRlZfH69RuuXL6h0XHndiilLcpo4qvqUI3EqHiexiSiylTi7+xHoy5NtXSG+t/l3Rv16dkPbkVQ2lIdXpWpRPlOCYChkSGCTNBJu8KqLypWsvni7xKAhVV5OnRtw5H9p3SeAaCyQ1WeRifwLDv9bjj70aBrEy2ZsFzp9+hWBKVypf+XorFDXcxMS3xW2H+j/gM9vnH0jH7feF9unHSlQ3a5ofGNN7q+kZci9WqQ+SSezNgEyFSS4XaRYh0//v3/v0aWKBb437+B1DD4PDoAmaIobn5/QRTFYFEUL4ui6AM81xNGBN7PbzEDFB9SYmVlQUxsjlhcXDzWVhY6MrHZMiqVioyM55QpozuMmBcX5/3Extzi+YuXPHgQSVxsvOaeIi4BSyvzPHrMNTIqlYqM9BeULlMKE5OiTJg0lj+X6h/6zYuFZXni4xI1vxMUiZhbltOSMbcoR0K2jEql4kXGC0qVLknY3Qg692iPXC7HpoIVderXwtI65zmXrZ3P2QsH+WWy9rQAU/NSpCtyjm3PiE/BzLy0zrM1H96FqRdX0X3GEJzn7/0oe/JS1qIMzxTPNL+fxSdR5iMrp/s37xPsH8LhwIMcDjpI4MUgYh7G6JUtb1mOBEVOOj6Nf6aTjh9DnQa1MDQ0JCYqZ/TE0tKCuLg8/mCp7Q+WVubExSYA+vzhB/7S4w+iKHLi9C7OXzrFyG+/yo7Hglgt34vHSo+u2Ny+l/Gc0tk+3rhxfa4HeOB/w52J42drGgoymQw/fxceRQVw4fwVMtKfEx+XoIkzQfEUizx6zC3LE6/Isel5tt+5n/Xm1avXXA/15krIObZt2EN6WoZWWGtbK2rXrUl6WjqKXHriFYm6aWdpjiIuPpee55QurW6YVahojdelE5xy3UuzFurGa+TjJ1StVgnbClZYW1tQrLgJVjbqciA2Lh6rvGWCdU65oVKpSE/PoEyZUjrlSWxcPFbWFpr0CgzwJD7uNj4+l7gRcEsjt3bjUkIfXqVa9crcuHYTRWyOfQqFbllhaZmnrMh4TunSpbLts+H85dOcddtP8xaNyUtB+F5FO1uSklJYv/lPfP3OsGb9YuzsbD47nypXtUMEDp3YhufFE/ySa8rSe0zNStC1ewfuXckZ7StlUZrk+CTN75T4ZK2GQ146fNVZM9oAUNqyDMs8VrHu2jacN5/SGi2AwqsvHj+MLpB3ae7i6Sybv0qnI+M9pcxLk6LInX4plDLPP/3aDu7EnVzpZ2hsxNyzfzL71FIadG2ab7iC5N+o/wCsrSyJjcl5r+LiErCytswjY6FVzqZnZHyUb+TGoHwZlAk59Z8yMQlDPXlUvGtrKp7ehOXqWRhYlNVcF4yNqHBsLbaHV1Gs0/9ug+K/jjSV6POoAwR9YpjRgJsgCK+BDNTTjXQQBOEH4AeAwV+N1Lmft5dZ0O04+qi9dXs5DcPY2Jg9u9fqDB3rjUOPIlEUmTFrAps27NL0OH6QfOLRFtEvc/zgWapUr8Qp733ExcRzMyAEpVL9ITjlx9kkJjyjWDET1u/6G8UzuHXy8kfrBLi2z4tr+7yo37slHcf15diUzToyX8K+/LCys6RC1QoMaToMgGUHl1K3WRB3rt/9GDWfvKdy2fJlWLxuLrPHL9IK+zFx55dHM2aNZ9N6/f7Qo8vXJCQ8pWzZ0pw8u5uIiMcfpwu9QgAEBobQrEl3qteowpaty/Hy9OXt23dkZWXRukUvzMxKcODQZl6m6LbVP9am+g3roFKpaG7fBbOSphx13YXfxWvERKsbUybFirJp9wr+mPU3KnQ/avLOE9WvBxITntGoTidSU9OoV782uw6sp10LJ9LTM/htygK27FyJmZkpL1+80vj9x9uRv30AWVlZNG7SFTMzU04c24G9fQ3u3VP3iI//+XdkMhnLls+hafOG+cbxj/oRSUx4ioN9e1JT0qjvYM/egxtp1awnL56/zBVWJ+j/t+8ZGMip72DPjGl/EBQYwtI/Z9O9V2cy0rV94mPzyUAup1nzhnTvMIjXr99w7MwuQoLv4XfpGgByuZzN25ezfct+nsbkfATq8+P83tlW/dpRqW4V/vgqZ2A5JT6ZGd0nUbJ8KaZs+53rblfJSEr/YLpo26Sr61Pri5q1q36Enk97l6rVqEJSUgp3Q+7TrJVugzG/h8/v2Vv0bYtdvSos+2qO5trUlmNJe5pKOVtzph+aT2xYNM+eJOoNX2AUUv3Xd7Aja7bv/Ce1H633k/iIOF74XuO5qy9iZiZmX/XEYulUYr9Vr/l43HE4qmcpGNpYYLP7T2IjosjM1aD5r/G/uSeRNGJQmEwCeoqiaAPsAlbqExJFcasoio1FUWwcH5+KrU3Ogjdra0sU8doFWVxcAjbZMnK5HFPTEqSkaE/fyY+3b9/i4upF9ZpVsLbJ6T2wsrYgIf6plqwiLkEjI5fLMTUrTmpKGo2b1GfBH9MJuefLTz+PYvLUnxgzVt9MKjUJikStXg4LK3OeJiRpy8Q/xSJbRi6XU9y0OGmp6ahUKpbMWUnvDkP4acQUTE1LEP1YPXcxMbuX4uXLVzif9MC2fhVNfBkJKZhZ5fRamFqWJuOp/ik6ALed/andJZ/K6QMkxSdRziqnB6icZVlSElM+Kmyrbq0IuxXGm1dvePPqDQEXAqjZQP+czkTFMyxy9dSWtyynk47/RLHiJqzfv5z1f27lzs17WvcUigSsrfP4Q4I+f1D3Rub2h0aN6zP/j+kE373Ajz+PYtKUHxn9g7qh8z6OpKQUXJ29aNSoHoq4BGy0fM+S+Ly6FDky+fl4RPgjXr58Re3a2o3c9PTn+F2+jm1FKyytc3pPLazKk5hHT4IiEUurHJtKZPtdn4E9uHT+KkqlkuSkFAKvB1PPwR5QT6/YtHslZ467cc7FB4UiUdMLD+rebZ13SZHTW6fWU4LU1DTevcvUTL27HRJKdFQMVarYAeDl4UvPzl8z/ueZyGQyIh9FA2BjbUl83jIhNl5TbsjlcszMTElJSSUuLl6rPLGxtiReoR02PT2Di5eu0q1re63rWVlZnD7hRp26NTWjFaDugdZnn3We/EpNybYvO99Cgu8RFfmEqlUr6Yb9wr6niEtAEZdAUGAIAGfOeGBhXv6z80mhSMT/SgApKWm8fv0GH69L1KufM6Vj+ZoFPH4czbZN2qOOKQnJlLHM6R0tbVmGVD1lQ51W9ej760BWjF6qmT6Um7SnqcRGPKFmU+1pJHnzt6DqiyrVK3/xd6lRMwc6d2/P5VturNv2Jy3bNOGHVeO14kxNSKa0Ve70K03aU930qyUk/bAAACAASURBVN2qHr1+HcCaPOn3foTlWUwiYdfuUdG+kk7Ygqaw6r96De214oyNi8fGNue9sra20IzoaMnkem/NTE0/2jfeo0xMwsAip/4zMC+LMk8eZaU9R8xUT81NP+aBsX01zT3VM7VsZmwCr27cxrhWFSQKH6lh8HncAxp9UCobQRDKAfVFUbyefekI0PJD4QIDQ6ha1Q47O1sMDQ0ZPKg3Li5eWjIuLl4MHzYQgP79HfH1vfKPcRYrZoKFRXlA/fJ379YR/ysBVKlSkQoVbTA0NKT/QEfc3Xy0wnm4+fDNUPXipz79unPporp3rGfXb6hv35769u3ZtHE3K5dvYtuWffnqv3MrFLtKtthUsMLQ0ADHvl3x8bioJePjcZH+X6nXbXd36sQ1vwAAihQtQlGTIgC0atcMlUrFw4hI5HI5pbKnYhgYGNCha2sSInKm4MSGPKKsnQWlbMohN5RT36kF9720B3zK2OVUdDU6NiApSrvQ/FjCQ8KxtrPCwtYcA0MD2vVuh7/XtY8K+1TxlLrN6iKTy5AbyKnXvG6+U4nuBd+nQmUbrCtYYmBoQPe+nbno6fdRegwMDVi1axnOx9zxcr6gc/9m0B0qV7HL8YcBjni4avuDu5sPXw9RL5Lt07c7l7P9wbHbEBzqdMChTgc2b9zNqhWb2b51PyYmRSlevBgAJiZF6dCpNfdDIwgKuk3lKnZUzNY1YGAv3Fy9tXS5ufrwzVD1Qu2+/Xpw8aI/ABUr2iCXywGwtbWiWvXKRD+JpUzZ0piZqecAFyliTPsOrfDzvY5d5QrYVLDG0NAAp37d8XbX9jtvD18GfN0bgB69u+CfPV88LjZBM8+3qElRGjSuy6MH6sWCf66dz8OIx+zYpPb54Jt3qFylIhUqWmNoaEjfAT3xdNdOY0/3Cwz+Rr0At1efblzJ7mkuU6YUMpm6SK5Q0YZKlSsSHaVeC1K2rHrqW+SjaCpVqcB578vqMmFwH5xdPLXid3bxZPjwQQAMGODIhewywdnFk8GD+2BkZISdnS1Vq1biRsAtypYtjZmZaXZ6FaFTxzaEZy/Cfd8wAejWoyNBASFUrpzjG/0GOOKhU1ac5+tv1GVF777duZydX7ntq2hnS+UqdkRFaft3Qfje06dJxMXFU7Wa+kOwXbsWBAbc+ux88vXxo5Z9DYoWLYJcLqdFqyaaRcu/zZpACdMSzJmxlLw8CnmARSVLytmWR25oQAun1gR5BWjJVLSvxPdLf2LF90vISM4ZDShtUQZDYyMAipkWo3rjWsQ/itMKW1j1RYB/0Bd/l/7+Yy0t63alTYOejBvzG1cvB7B10lqtOCNDHlLezpKyNur0a+rUmltegVoyFewrMXLJWNaOXsbz5JzpfiamxTAwUk+QKF6qBNUa1USRa9F3YVFY9d+D+4+04lT7RqUc3xjcR79vvC83PsI39PHmTjiGFa0wsDYHQwNMe7bj5QXt+k9eLmcab/GOzXmX3biRmRZHMDRU/7+kKUUb1tZZtPxfIwuxwP/+DaSpRJ/HeWCJIAhjRFHcBiAIQhPARBTFi3rkUwEzQRCqi6IYAXQB9G8fkAuVSsXEiXNwcd6PXC5n954j3L8fwdy5U7gZdBsXVy927T7Mrp2rCb13mZSUNIaPyFnRHx5+FdMSJTAyMsTJqRuOvYaSkpLKieM7MTY2Qi6X4et7le1bD/D4UTQnTu9CLpdzYN8xwu4/4PfZEwi+eRd3Nx/27TnK5u0rCArxITU1TWsXkPzYvmsVrdo0o0yZUtwN92PZ4jV4HPNkwe9/sfPoeuQyOccPneFh+GMm/PYjd4JDOX/uEscOnGH5xj/wvnGatNR0Jv0wE4AyZUux8+h6xCyRhPinTP1ZPUxsZGzIzqPrMTAwQC6XcfXSDcIPndc8R5Yqi7Nzd/Pd3hkIchmBR315+iCOzpMGEnfnMfe9b9JiZFeqtqqDSqnkdfpLjk3ZpAk/3W8NxsWLIjc0oHbXRuwcvkxrR6PcZKmyWD9nI0v2L0Yml3HuiCfREdGMmDKciNsPuOZ1jer1qzNv2xxKmJWgeedmDJ88nB86j+Wyqx8OLR3Y6rUZURQJvBjENe/revWoVCqWzlzJpkOrkMnlnD7kwqPwSH6ePpp7wWFc9PTD3qEWq3YuxbRkCdp1ac3P076nf7thdOvdiYbNHTArZUrvr3oCMHfCYsLvPdDEPX3qAo6f3olcJufAvuOEhT3k91kTuHXrDh5u59m/9xibty0nMNib1NQ0Rn876R99oVz5suw7uAFQV17Hjzrj430ZVZaKaVPmc+rMHuRyGfv2qn1v1uyJ3Lx5B3c3H/buOcLW7SsJvn2e1NR0vh2p7kls0bIxkyb/SKZSSVZWFpMnziUlORX7OjXZvPVv5HI5MpnAqRNueHv4olQq2XtsEzK5jGMHT/Mg/BGTZvzMneB7eHtc5Mj+U6zatJgLAc6kp2UwbvR0APbtOMzf6xZy7spJBAGOHzxDWOgDGjdrQP+vnAi7F4Gr7xEAFi9cxcxpizh0YjtyuYxD+08SHvaQ6TPHEXzrLp7uFzi47zjrt/yJ/00P0lLTGfudenvQ5q0aM/338ShVSlSqLKZPnk9amvrj8I9lM7Gvox4N2bJhD3+tms9fAuzec4TQ0Ajmz5tKYFAILi5e7Nx1mD271xIW6kdqahpDhqm3rQwNjeD4cWfuhFxAqVIxfsIssrKysLQ0Z+eO1cjlMmQyGcePO+Pq5o0gCOzasZqSZqYIgsC9u2FMnTSPSxf9OXZqBzK5nIP7jhMe9pAZs8YTfPMuHu7nObD3GBu3/s2NYC/SUtMZk+0bLVo1YcasCSiVKrJUKqZOnEtaas7Hb0H5HsBvU/9gy/YVGBkZEhUVw+RfZuN36fpn5VN6egZbNuzG4/wxRFHEx+sS3p4XsbQyZ9K0H4kIf4TXJfVi+av7z+N7WN3QzVJlsXvuNmbsnYdMLsP3qA9xD2IYOPkbHt9+yE3vAIbOHEkRkyKM3zgNgGTFM1aMXopVVRuGzR6FKIoIgoDr1tPEhGt/NBVWfbFvx1GiHsd80XfpY8hSZXFg7nam7J2DTC7j8tHzKB7E0HfS10TdeUiwdyCDfx+BsUkRft6ozqvkuCTWjlmGVVUbRi4ZS5YoIhMEXDed0trN6FOYNm8ZAbduk5aWQae+w/j5++EMcNK/fWxeVCpVodR/R/ad0tE7ceIcXF0OIJPL2LP7CKH3I5g3dypBN9Xlxq5dh9m9aw2hoX6kpqQxbHjOdrcR4f6Ymqp9o7dTNxwdh2jtaJSjKItnizZis30xyGRknPTk3cNoyowbzpu7D3h54RqlhvWhWMfmoFShSn9Owu8r1HZUtsV8wXjIEkEmkLLt6H++YfC/ivDJc8gkABAEwQr1dqWNgDfkbFe6E6gJFAeSge9FUTwnCEI/YCGQhbqh8J0oio/1RK3BuIhtoWSOiYFxYagBoGxRs0LRk3u70oIkSPVx04S+BImZGR8W+gLEvHz2YaEvhDJL9WGhL0CZIp+3i8in8lr1rlD0ACS9Khx/KFmkWKHoKcwdOIzkhdMn1tHsA9s7fkFOJAZ+WOgLYFVMd+OGgqB9Cd21DAXF1sC/Pyz0Bahda1Ch6AGIziic9RN3K9cpFD0A1e976Fkt8e/RwrpDgRda/nEXCt1macTgMxFFUQHont4BbfRcQxTFU6i3OJWQkJCQkJCQkPg/zP9qx7q0xkBCQkJCQkJCQkJCQhoxkJCQkJCQkJCQkPgU/q3FwQWNNGIgISEhISEhISEhISGNGEhISEhISEhISEh8CnkPRfxfQWoY/IcpZlikUPRkvP3IU4u/AJVKWHxY6AuwOy24UPQ8f/e6UPQAVCxRvlD0vChEmwqLhFefdlDP55Il6p58/H+d9DcvPyz0hSisalam7yjYAiCi6McfOvj/SwmjooWiJ1MsnJ3Egt983lkyn0Nh7RYUev9YoegBqFFzQKHoGZJWeOVD4ey7JSE1DCQkJCQk/nX+N/veJCQk/leRdiWSkJCQkJCQkJCQkPifRRoxkJCQkJCQkJCQkPgEpF2JJCQkJCQkJCQkJCT+Z5FGDCQkJCQkJCQkJCQ+AWmNgYSEhISEhISEhITE/yzSiIGEhISEhISEhITEJyCtMZD4V+jUuQ3Xb54jMNibCZN/0LlvZGTEjt2rCQz2xuv8cWwrWGvdt7ax5El8ML+O/x4AY2MjvC4c59L/Y++946I6ovbxZ126AiJI2aUqWEGQoqIoRUDpKIoFayyxG6OmWxJrNEZjiyWJsReQXsWGYKNI7ywsZRewYdcIeH5/LFxYWGN5hbzf97ePn/nIzpw5554zZ87cOzN37o1wZOZeRQk/GQV5Sfhq9WKJvE+d/B0FeUm4kRQBAwNdpuzrr5agIC8JuTnX4OpiDwDQ1eXg4oVAZGddRWbGZSxdMoehP3Xyd6SmXMDp+COITA7E6fgjAIDhjkMRnHgKYTfOYNaSae2uwXKYOU5e+BPJlVcx2sOBydfR1cLJuD9xOv4IAq8eh98Mn3Z1HUfbITElCjfuxGLJF3Ml6CeLA3/twI07sYi6eAa6+hymrP/APoi4cApXb4bj8vVQyMvLAQBkZWWxfdd6JKVGIzE5Ej4+YwEAzi6jcCfjEjKzr+DLlQsk2vLosT3IzL6CKwkh0G9qJ0cnOyReD8ft5BgkXg+Hvb0tU8fPzwO3bscgJTUOGzZ+046nneMwRF4/h5hbQZi7dEa7cqthFgiMP4pMwXW4ejqJlR08vQs3iy5i34kd7eoBgKurA3KyE5CXl4TVqyT7xskT+5GXl4SkxBbf6NGjOy7EncPDB4XYtWsjQ6+oqIDQ0KPIzrqKjPRLOHni94/iDwBfrV6MvLwk5GQnwKXJ9wBg2bK5yEi/hPQ7F3H82F7Iy8uLbOw4AjduRCE39xoePixAYeF1rFq1UKLM48f3IicnAdeuhUJfXyTTyckO169HIiUlDtevR8LefjhTZ/361Sguvol79/JabOfigOysq8jLTcSqVYskyjlxfD/ychOReC1czHZxcWfx4H4Bdu3cIFbnwoVzyM66iuTbscjPS0JebuIn67cAcPjQDgirMpGRfkmMl7n5QCQlRqCw4AaePuGhrDQFq98i8+TJ35Gfl4TrbWR+9dUS5OclISfnmlh7FRfdQvqdi0hNuYBbN6OZ/DGuDsjNudYpcakZn9rf3wZbxyE4n3gSITdOY+aSgHblg4eZ48SFP3Gr8opYvNPW1cLxuD9wMv4vnL16TGK8awsn55G4lRaL5Ix4LFshaeyQxR9HdiE5Ix5xlwOZsUNPn4vK2ixcSQrDlaQw/LLzx3Z1HUaPQMLtCCSlRmPx8vb2lJOTxf4/f0FSajQi4k9BV08UW8dN8EBcQhCTKu5nYYBpX7G6f53cg4vXQyTqNNxxKEKSTiPs5lnMfst4cerCX0ipSoCzpwOT3zxenLn4N4ISTmDCDN92dUc62SLu5nlcTA7F/GWzJOq06/AWXEwORVDsUXD1dAAAsrIy2Lp7HSITziL8ymkMGW7F1DkRehBxN88j/MophF85BbA+7Jbrh82/YpTHZPhOaz+mvA9GOQ3HxVshuJwchgXLZkvUafcfW3E5OQzBcccYnWRkZLB970+IuXYOF26cx8LlnzF1PlsQgNikIMQkBuK3Q1sg1zQ2NqMzfVyKjoH0weAjwWKxtFks1hkWi8VjsVh5LBYrmsVi9WGxWLEsFusRi8WKbEPvxGKx7rBYrBwWi3WUxWK9c7WmS5cu2LZjPfzHz4WtjRv8Jniib19jMZppMybg0aMnsLZwxu/7jmD9T6vFyjdv/R6X4q8xv//55zV8PWfAwc4XjY2NEAhqMGful5g0yRf9+5uI1f1s9hTU1T1GvwF22LX7MLZs/h4A0L+/Cfz9fTDIwgkengHYs3szunTpgoaGBqz+6keYDXLACDsvLFw4i+E5NWAhrG1cMcVlNi5FJeBydAK6dOmCrzd/iaUBq+BnPw1jfZ1h1MdQ7Bqqq2qxfvlmxIZcFMu/V/sAs7wWYIrLbMxwn4/ZS6ZBQ0tdzHabf/kBARM+h/1QL/hOcEefvr3FeEyZ7ofHj55guOVYHNp/FD+sXwkAYLPZ2HvoZ3z95Y9wsPWGn+dM1Nc3AACWr/oc9+89hJ21O0YN9UJS0m106dIFv+78CeN9Z8Ha0hUTJ3qjXz/xdpo5yx+PHj2GuZkj9u35k7nRf/DgISZOmIuhQ9zw+bxVOPznrwBENxwbN38LT48A2FiPgaamBoaOtBbT7/utq7Fg6hfwHjkZ7uNc0buPkbjtBLX4fvkGRAVfQFv8tf8Evl2yvl1+M+/fftsIL+/pMDd3xKRJPujfT9w3Zs+ejLpHjzFggB127z6MzZu+AwC8evUP1v+4HV9/s6Ed3507D8JskAOGDnOHp6cLtm3f98H8+/cT+Z6FhRM8vaZh9+5N6NKlCzgcbSxe/BmG2XpgsKUz2Gw2/P29AQB792zBnDkrAADbt+9HYuKtpjYSlzlr1iTU1T2Gqak99uz5E5s2NbdRHSZM+Aw2NmMwb96X+OuvnUyd6OiLGDmyZQBrtp23zwyYWzhhkr9POzmzZ03Go0ePMGDgSOze8wc2bWyx3Y8//oJvvpF8gzlz1jIMs3UHAHh4BsDM3PGT9FsAOHbsHDw82w/iWzd/j02bd4KIsGTpdygtLcfkt8h8VPcY/QfY4bfdh7G5lcxJ/j4wt3CCZxuZAODsMhHWNq6MXl26dMHu3zbB02vaJ9NPYlxq1SYd5e9t0RzvlgWswkT76RgjId7VNMW7uDbx7n7tA3zmtRABLp9hlvvnmLkkQCzeSZL18451mOQ3DyNs3DF+gme7+BcwYyIePXqMIRYuOLDvb6z7sWXs4JdVwNHOB452Pli1Yl073hu3/YDp/gvhaOsNHz93mPTtJUYzedp4PH70BHbW7jj8+3F8t/5LAEBIUBTG2E/AGPsJWL7gW1RWCJCXU8jUc/N0xovnkj+42aVLF3yzZSWWTF0Jv1EBGDvOGb3ajheCWqxbvgmxIfFi+c3jxWTnWZjuNg+zl05DTy0NMd7rt36DuZOXwW3EBHiOGwPjNvF0QoAvnjx6Auchvjhy4CRWr10GAPCfPg4A4Gk/CbMmLsK3P60Aq9UH9FYu+AHejlPh7TgV+MAPIPq6u+DAr+9+4JSELl264Mefv8HsSUswZoQfvMaPhXEf8XbyD/DFk0dP4TTEB38dOImv1y0HALj7OENOXg5uo/zhPToAU2b6gaunAy3tnpg5bwp8nAPgNnIiunTpAlef0WIyO8vH/zeAOuHffwHpg8FHgCXq9SEArhJRbyIaAOA7AFoAtgOY3oa+C4CjACYTkSmAcgAz3yXHynoQykrLUc6vRH19PYLPR8HNc7QYjbuHM86cCgYAhIXGYpRDy4yzu6cz+PxKFOQXi9V5/vwFrKwHgc+vxJs3b1BfX49z58Lg7TVGjM7byxXHj4u+1Hj+fBScHO2a8sfg3LkwvH79Gnx+JXg8PobYDEZNzV2kZ+QAAJ49e46CgmJwOe2/dOzi5YjY0IswHdwfVfwqCCqEaKhvQFzYRTiMsROjra6qQXE+D2/eiAfUhvoG1L+uBwDIycuC1UXclQdbmYFfWoGK8irU19cj7HwMxriLz5qPdXfCudOhAIDIsAsYaT8MAGDvNAL5OUXMgFVX95iRPzlgHHbvPAxA9OLRgwd1sLY2RymvHPymdgoKioCHp4uYLA8PF5w8cR4AEBISAwcH0axzVmYeaqrvAgDy8oogLy8POTk5GBrpo6S4DPfvPwQAXLlyHa4ejgw/M8sBqCyrQlW5EPX1DYgOjYfj2FFiMoWV1SjKKwG9aT8Y3U5MxfNnkgdgGxsL8Hh8lJVVML7h5eUqRuPV2jeCo+DY5BsvXrzEjRspePXqHzH6ly9fISHhBgDAwmIg7t67DxkZmQ/m7+Xl2s73bGwsAAAybBkoKiqAzWZDUUkR1dW1AETtNHToYPB4fNTXN0AgqEFgYAQ827SRp6cLTp4UtVFwcDQcHEYAADIzc1EtoY0AIDk5HTU1d99uu8BwybqdCGqSEwVHxxHitvtH3Hbvapv/ab8FgMSk23hY1/7r0ESEwRZm4PH4ePXqFQTCGpw9FwavNjK93iLTy2sMzr5FpiQMsRn8yfWTFJc43Ja41BH+LgkDB/dHJV8AQUU1GuobcCHsEuwlxLuSfB7evBG/IWgb77p0+feh27LN2BFyPgpuHs5iNG4eo3HmtGhmPjw0FiNbjR3/BgsrM/DLmmNrA8KCY+DqJh5bXd2dEHgmDAAQFXYBdqOGtuPj4+eOsPMxzG+lroqYt2gGfttxUKJc08H9UVnWarwIvQSHMSPFaKorm8eLf7cfq82XrwdZDkQ5vxKV5QLU1zcgKvQCRrs5iNE4u9kj+Kxovi824hJsRw4BABj37YUb15IBAA/v1+HJ46cwsxggUYcPhbWFGVRVlD+qrrmlKcrLWnSKDImDSzudHHD+TAQAICb8IoY36UQEKCmJYqmCgjzq6+vx7KnoC8dsGVGeKM4q4F5ty9e9O9PHpeg4SC3/cXAEUE9EB5oziCiDiBKJ6BKAp23o1QH8Q0RFTb/jAbzze+U6OtoQCKqZ30JBDXR0tMRpOFoQVIk+Hd/Y2Ignj5+hh7oalJQUsXzFfGzbsqcd3y5duuDQXzsxwm4Irl65juSUdFQJqsFpcxPP4WqjskrI8H78+AnU1dXA4bTkAxDV5YrXNTDQhYW5KW4np4vlWw4zx8P7dagsq0JP7Z6oEbTcVN2tvgdN7Z7vMgsDLY4mzl76G9FpwTi69yTu1z5gyrR1tCAQ1DC/q4U10NbRFKuvraMFoaCV7Z48RY8e3dHb2AAEwunzh3AhIQiLlomWUVVURQH66++X4kJCEA79vROamhrgcLRR1aqdBIKa9rbkaDE0jY2NePzkKdTV1cRofH3dkJWZi9evX6OUx0efvr2hr88Fm82Gl5cLtLktba+lrYlqYS3zu1Z4F1ofYLt/A5ejg6rKNvpwddrQaKOqqrU+T9rp8zaYGPeCmpoqrlxJ+mD+HK4Okw8AgqoacDk6EAprsHPXQfBKbqOi/A6ePH6KixdFK2WfL1iNbdvWYvhwG0ydOh6//PI7BIJqcLlt20gbVa38/YmENho3zh2ZTW0kCW37hkBQ3e7h+H3kSMLhQztw7OheMdpP3W/b4stV67BkyRwMH26Dn7euwQ8/bJGs01tkclvp2myPZplEhJjo07h9KwZz5wS049MR+jXHpeRWcamj/b0Zmto9Udsu3mn8Sw1xaHE0cfrS34hKO98u3rWFjo4WhFUt8U8orIEOR6sdjaCVTqL4J9JJ30AXlxNDER59AsNsrdvU00R1q9haI6yFTrvY2kIj4v0Maj26i9F4jRuLsOCWLWSrv1uKQ/uO4uWLVxJ10tTpiVphi/1qq++ip84HjheXjyImLQR/7zspdkMrut6WeFojrIVWG95a2j1R00TT2NiIZ006FeQUwdnNAWw2G7r6HJia94dOq1i9dfd6hF85hcVftt/O2pHQ1hEfI6ol6dSmnZ426RQTfhEvXrzCrdx4JGXE4PC+Y3j86Alqa+7hj33HkJQRg1u58Xj65BluJ6Qw/DrTx/834A1Rh6f/AtIHg4+DKYC0D6C/D0CWxWI1R9gJAPQkEbJYrPksFiuVxWKlNrxpP6Pb9nistjMfzTTffL8Mv+89gucSlmXfvHmD9T/8jPNBkbC0GoSBA/t+AO+3y2xG165KOHf2ML5ctQ5Pnz4Toxvj68xsC3oXn3ehVngXk0bPgo/tJHj6j0UPjZaBWiLvNr/fJp/NlsGQYZZYPO8r+IydBjdPZ9iNGgYZNhtcXR2k3E6Hq/0EpKVkYNPm795Lj3fR9O9vgp82fo1lS0XbIh49eoIvlq/B0eN7ceHiOZSXC9DQ0NiKYXt7fKplRwmX+sH6vA1sNhtLl81Ffl4RysoqPpj/266te3dVeHm6ok9fWxgYWqFrV0VMnTIeALB82Txs374P586F4/jxQPz885qP0ql/fxNs3PgNliz59q36vZ8vSNbh3zBr1jJYWbvgx59+gZZWTwQEtMwrfKp+Kwmfz5+B4ycCce5cGFat/hGHDu74ZDLtHXwxZOhYeHpNw8KFszDSbuj/oC99fFzqSH8XZyJJzvtXrxXexZTRs+BrO7ldvGsn6mPtCEJtzV1YDHSA00hfrPluCw7+uQPdlLu2rvhxvFvRDLYyw6uXL1GYXwIAGGDaF4ZG+oiNutSu3r/J/RAD1grvYpLTTPjYToKXv5u4/f4HOgWdCkeNsBYhF4/j+40rcSclk4nVKxf8AE/7SZjiORfWwwaDJd/tva/3f4z3MNfbdDK3HIg3jY2wNXWFvZUH5i6aDj0DLlRUleHs5gB7K0/YmrpCUUkRbn6tVtc60cel6DhIHww6ASSKMJMB7GSxWMkQrSg0vIX2EBFZE5H1vdon4LaaueJwtcW2LQCiVQSurmhWjM1mQ0W1G+oePoKVtTnWb/gKGTlXsGDRLKxYuQBz57e8rCUU1kCzpwauJ97GGFcH6HJ1mK0XzRBUVUNPl8PwVlVVwcOHdRAIWvIBiOo2zUzIyMgg8OxhnD4dgtDQGDF+bDYbTu72uBAuCv53q+9Cm9sy06Sp01NsFud9cb/2AUoLyzB4qDmTVy2sEZsR1uFoo7Za3HbVwhpmRpHNZkNFRRl1dY9RLazBzespePjwEV6+fIXL8ddgZj4ADx8+wovnLxAdIXqwiQiNg4XFQAgE1dBt1U5crnZ7WwpqGBo2mw1VFWU8fCjausHhauPUmYOYP3el2M1yTPQlONqPw2hHPxQXl6KitJIpq62+KzYDqMXRxN2aD7edJFQJqqGr10YfYU17Gt3W+qgw+vwbft//M3glZXj8pGVR7UP4C6pa8gGAq6sNYXUNRjvZYpiMrgAAIABJREFUgc+vxP37D9HQ0IDQ0BgMs7WChkYPmA3qj2vXbkFXVwdBQREYNswKXK4OhMK2bVQN3Vb+rtKqjbhcbZw9ewhz534p1kZt0bZvcLk6EEryhbfIeRuETfbh8fioe/QYNtai7VOfqt++DTOmT0RIcDR0dTkICoqAjY2FZJ3eIrOqlU2b7dEss/m67917gNCwGNjYWIjx+ZT6/Vtc6kh/b4271feg9YniHa+QLxbv2kIorAFHtyX+cTjazJbF1jTcVjqpqCij7uEjvH5dj7om3TIzcsEvq4Cxcct++2phLXRaxVZtjhZqau6J8W5NI+LdDY/qHjPl3uPdENpqG5GVjQXMzAfgZkYcQmKOoVdvQxwOFl/tviu8Cy1Oi/20dDRx7yNi3r3a++AVlsFyWIv9aoS1YrP82hytdvG0pvous2rLZrPRrUmnxsZGbF7zK7wdp2LhjJVQUVFGeakoRtQ22eX58xeICI4FS0b+g6/3Y1EjFB8jdDhauNumnWratJNyk07efm5IuHQDDQ0NeHC/Dmm3M2BmMQAj7IeiqlyIhw/q0NDQgLjIyxhkbcrw60wf/98A6TsGUrRGLgCrd1K1AhHdJKKRRDQEwDUAxe+qcyctG716G0LfQBeysrIY7+fRbkYlJvoSJk8VzYz6+I5FYsItAIDHmKmwMHWEhakjDuz/Gzt3HMAfh05AXaMHVFSVcSctG72NDeE61gE8Hh/+/j6IiBR/STUi8gKmT58IQHRCzpWr15l8f38f0V54Qz0YGxshOUW0NH/40A7kF5Rg12+H2unjPHok+CXluFstCk65GQXQM9IDR08HMrIyGOPjjIS46+9lT02dnpBXEO3zVlZVhrnNIJTzWm7YMu7kwKi3AfQMuJCVlYWPnxviYq6I8YiLuQL/KaLTKTx9XJF07TYA4Oql6xgwsC+zX33YCBsUFYpmti7EXmX2YdrZD0NBQQnS0rLQ29gQBk3tNGGCF6KjxF+sio6+iIBpolnecePckJBwEwCgqqqM8+f/wvq123DrlvgiVM+eohevundXwbz50xB0Mowpy0nPh34vPXD1dSArKwN3XxdcibuGT4HU1EwYGxvB0FAPsrKy8Pf3QWSk+Mt8kZHxLb4x3gNXr7673X5cvxqqqiqYMXPpR/OPjIxv53spKRmoqBRi6NDBUFRUAAA4OtqhoKAEdXWPoaqigkePnsDY2AgTJ3qjqIiHiRO9EBUlLjMq6iIzEz9+vDvzToSqqgqCg49g7dptuHkz9T1sZ9ii20RvybpNm9Ak5922Y7PZzLaVjIxcGBnqo6bmLmO7T9Fv3wZhdS0UFBVgbGyEKZPHgcfjY5K/DyLbyIx8i8zIyAuYJEGmkpIiunUTzUIrKSnCxdkeubmFSEnNaOcbHR2XOsrf2yIvowB6RrpMvHP1GY1rcUnvVVc83nWDuY0Z+Ly3P6Cmp2WjV6+WsWOcnwdio8XHjtjoy5g8RfTirLfvWCQ2xSR1dTVmf7eBoR569TYEn98yKZF5JwdGvfShp8+FrKwMfMa7IT5WPLbGx1zBxMmil/I9fFxxPfE2U8ZiseDp44rw4JYHg+NHzsJ6oBNsLcZgnNsMlPL4mDd+qRjP3IwC6PfSBUe/abzwHY2rFz7GfsqwsDEDv6TFftnpeTA00oOuPgeysjLw8HXFpdgEMR6XYhMwfpInAGCs12jcShJtoVFQVICikijujLAfisbGRpQUlYHNZjPbp2RkZODoagc0St6C2BHISs+FYS99RifPcWNwMfZqO538JnsBANy8nXEzUaSTsKoGw0faAAAUlRRgYT0IpcV8CKtqYGFtBoWmODt81BDwi8sZfp3p41J0IIhImj4wQbRgdhvAvFZ5NgDsm/52ABDZpo5m0//yAC4BcHqXHLVuxjRx/BwqLi6lUl45bVi/g9S6GdO2LXtoiv98UutmTNrqAyg0OJp4JXxKTckgC1NHUutmLJa2bvqN1ny3hdS6GdOIoR6UmZFLOdn5VF5eRQ/uP6SSkjL6Yc1WYstyaMPGX8ln3Exiy3JIqZsRBQZFUHFxKSUn3yHjPsOILcshtiyHflizlUpKyqigsIQ8PAOILcuhUfY+RESUmZVL6Rk5lJ6RQ55e05g6fx89Sxu/2kaDtUcwacnUlcQvqaCKsirau+UgDdYeQQd3/EXLZ3xFg7VHUMCYOVQjqKUXz19Q3YNHVFJQSoO1R9AC/+VUlFtMhTnFVJRbTBtW/SzGV1u1P02d8DmVFJdRWWk5bflpF2mr9qcdP++jGZMXkbZqfzLQNKfwkFgq5ZXTndRMGjLIhbRV+5O2an9aPO8rKsgrpvzcItq76w8m39p0NN28nkK5OQV07epN6msynLoqGtI431lUVFRKPB6f1q/bTl0VDWnL5t9o4oS51FXRkHp070PB56OopKSMUlIyaGD/kdRV0ZB+XP8LPXv2nDIzc5lkqG9FXRUN6dzZMMrPK6L8vCKaOX0JDdAcIpY+n/IFlZWUU3lZJe3avJ8GaA6h/b/8QYunr6QBmkPI33UmVQtq6XmT7YrzeUzd1Jvp9ODeQ3r54iVVC2ppnv9SpkxWjkte3tOpqIhHJbwyWrNmK8nKcWnjxp00bvwskpXjUjflXhQUFEHFJWWUnJxOffrakqwcl2TluFRWVkEPHtTR06fPqLJSSIMGOZChkTUREeXnF1FGRg7xeHyqqbn7UfzXrNlKJbwyKiwsIU+vaUz+hg2/UkFBMeXk5NOJE0HUtZsRycpxacKEOZSdnU+lpeX0/PkLKi+vorVrt5GCgj5t2rSL/Pw+IwUFfVJVNaHz5yOb2iid+vUbQQoK+rRu3XZ69uw5ZWTkMElPbzApKOjTjh2/U1WVkBobG6mqSkg/bdhB3k224/H4tGbtzyQnr0sbN+2k8eNnk5y8Limr9KagoAgqadKtb7/hJCevS3LyulTGb2M7c0fqrmZCaWmZlJWVR7m5BRQeHitqm0/Ub9myHDp9JoSEwhp6/fo1VVYKae68L5k+nZaWSaWl5fTy5UuqrBTQD2u2kkyTTN9xM0lGlkNd28g06TOMZGQ5JCNBpowsh0z6DGP8PSe3gNGDLcshT69pVPgJ9ZMUl7y8pzN+0xH+3lxmpW0nlpZNXUX8kgqqLKuifVsOkpW2HR3acYRWzPiarLTtaPqYue3inZW2HS3y/4KKckua4l0JbVz1czve6somYmmS31wqKS6l0tJy2vjjDlJXNqHtW/dQgP/npK5sQhyNgaKxg8entNRMsjRzInVlE5oZsJjy84ooOyufMtNzaOrE+WJ8uWoDafrEBcQrLqOy0grauuE34qoNpJ3b9tOsKYuJqzaQemkPpojQWCrjlVN6ahbZWowhrtpA4qoNpAmesygtJYP53TYNHeRC+XlFZKE1vF0SjRflVFFWRXs2HyALreGi8WL6V2ShNZymjvmsnf0stIbT5xOXU2FuMRXmFFFhbjH9tHKrGF9jDUuaM3kplZbwqby0knZs2kvGGpa0Z/shmh/wBRlrWNIA7jCKDosnfmkFZaRlk6OVFxlrWJL9YA/iFZdRSWEpJV29RaMs3MlYw5LM9IdTdkYe5ecUUVF+Cf198BS9vsf7oLR80TwabjuUBvTvTyNH2NLpv/a/d10jdQuaPWkJlZbwiV9aQds37iEjdQv6bftBmhuwnIzULagvZwhFhV6gMl45ZaRl0yhLDzJSt6CB+rYUFXqBCvNLqKiAR5vX/UpG6hai+tsOUElRKRXkFVPw2Qgapu/YaT7+X9/7tU39etpQR6f/Qi9W082qFB8IFovFAbALopWDVwD4AL4A8BeAfgC6AXgAYA4RxbFYrO0APCFapfmdiHa9S0YPZZNOaZwn/0g+naYjMEjd6N1EnwDVLx92ipynr192ihwAMFDWfDfRJ0DxI0GnyOlMsLuwO0XOmw88jvB/gkYJp011BCRsG+4QdOZI1EXSfvUOwKAenRPvAID//N+3hX0qKMjIvZvoE6CnnGqnyAGAZ42SX3j+1MjLD+wUOQDQt987zzf5JOgh23nvTaRWJ3ZWOHov9NO06fCwVXA3pdN1ln75+CNBREIA/hKKRkrIAxGtBrBaUpkUUkghhRRSSCGFFFL815A+GEghhRRSSCGFFFJIIcUH4L86TrSjIX35WAoppJBCCimkkEIKKaSQrhhIIYUUUkghhRRSSCHFh4D+o+NEOxrSFQMppJBCCimkkEIKKaSQQrpiIIUUUkghhRRSSCGFFB+C/6vvGEgfDP4X45/G+k6RoyTbeV9jFLz4NF/nfRfk2bKdIqe7QtdOkQMA9W8aO0UOq5OOcgQAh56m7yb6BMh4UtYpcp504vG1jeic40o766jXbnIKnSIHAFTkOqff5j+ufDfRJ0J9Y0OnyOmsm6Hc5+XvJvp/DJ11hCgAFBac7xQ5GoYunSJHis6D9MFACimkkEIKKaSQQgopPgDSdwykkEIKKaSQQgoppJBCiv+zkK4YSCGFFFJIIYUUUkghxQeAOvFL950J6YqBFFJIIYUUUkghhRRSSCFdMZBCCimkkEIKKaSQQooPwRvpOwZSSCGFFFJIIYUUUkghxf9VSB8M/pfDxcUe6RmXkJV9FStXLmxXLicnh6PH9iIr+yquJoRCX18XAODkZIek6xFITo5F0vUI2NvbMnViYs8gPeMSbt6Kxs1b0dDoqQ5nl1FIS7+IjKzLWLFygUQ5R47uRkbWZVy+Ggx9fS4AwMpqEJJuRiLpZiSu34qCp5crUyc77xpuJscg6WYkriaGMfmOo+1wPTUGt9LjsHTFPAmyZHHoyK+4lR6HmEtnodckS0+fC35NBi4lhuBSYgi27VzP1AmOPIbrqTFMmbpGD9iPHoErt8NxLTUKi5bPkShn35/bcS01CmHxJ6GrxwEA+E7wQExCIJP49zMxwLQvunZTEsvPKL6G9Zu/BgA4jB6BhNsRSEqNxuK3yNr/5y9ISo1GRPwpRta4CR6ISwhiUsX9LAww7StW96+Te3DxeggAYKSTLWJvnkd8cgjmL5vZTo6snCx2Hd6M+OQQBMb+Da6ejihfVgZbdq9FRMIZhF85hSHDrZg67r4uCL96GlGJZ7F67TIAgKuLA7KzriIvNxGrVi2SoI8cThzfj7zcRCReC4eBgcjvevTojri4s3hwvwC7dm4QqxMRfhwpyXFIv3MRe/dsRpcu7cOPtYMV/rh6GEcS/4T/oontyk2HmmJv9B5El0XCzt1OrGzOd5/h0MUDOHz5IBb+2N6HP7Xfde3Wlcm7lBiCvNKb2L59LVxc7JGZeRk5OQlYtUpynz1+fC9ychJw7Zp4n71+PRIpKXG4fj0S9vbDmTphYUdx+3YM0tLiERz8FzIzr6AgLwlfrV4skf+pk7+jIC8JN5IimLYBgK+/WoKCvCTk5lyDq4s9k3/40A4IqzKRkX5JjNfPW35AZuZl5Ocn4f79fOTnJ73VH44f34fc3Gu4di2sjT+cwf37+di58yeGvlu3rrh9O4ZJVVUZ2Lj1O5EdnEfiVloskjPisWzFfInt9MeRXUjOiEfc5UCmnZrB1dUBX5iOxUs/Y/LmL5yBxFuRSLodhc8XifrNKKfhuHgrBJeTw7Bg2WyJcnb/sRWXk8MQHHeM6UsyMjLYvvcnxFw7hws3zmPh8hY5s+ZPQUxiIGKTgjD786kAOiaGN+Nc4GHk5SciPeMS8vKSsHqVZH84eWI/8vKSkJQo7g9frV6MvLwk5GQnwKWVPyxbNhcZ6ZeQfucijh/bC3l50ZHWR//eg9t34pCRcwX8qjtIy7yI5V9KaiM5/Pn3LqRmXET85SCJbVRRnYEly1piZUbOFSTdikRa5iUI7+V0ij6OjiNw+1YMUpLjcOVyMHr3NgQAuLo6ICc74YOvoUeP7rgQdw4PHxRi166N7eoBHeN3ny0IQGxSEGISA/HboS2Qk5eTKPtt+GHzrxjlMRm+09rHzffBaOdRSL0Tj/TMy1jx5ecSdBLdP6RnXsalK+eZ+wdLq0FIvBGBxBsRSLoZKXb/oKqqjGMn9iLlzgUkp8XBZsjgj7q2jgQRdXj6P6vY/8UEQBvAGQA8AHkAogEMAXATQC6ALACTWtEbAbgNoBjAWQBy75LRrasR8Xh8GtDfjlRVjCkrM48sB48mJUUDJi1f/j0dPnyClBQNaMb0JRQYGEFKigZkO8ydevWyISVFA7K2ciGBoJqpk5Bwk0aM8GR+q3brTaU8PpkNGEU9VPtQVlYeWVu6kLKSEZNWLF9Dfxw+ScpKRjRrxlIKCowgZSUj0lTvT92VjUlZyYiMew2hu3fvMb/5/Eoy0LMU46PdvT+VlZaTzaDRxFU3pZysfLKzcSdNlb5M+urL9fT3n6dJU6UvzZ+9gkLPR5GmSl+yMnWi/NxCMdrmlHTtNrnY+zG/DdQHEb+0gkZYjKVemhaUm11ATsO8SU/NlEnfrdxAx/86S3pqprRozioKD44RK9dTMyXn4eOovKyyXb6emillpefSePcZpKduRmWlFWRrMYYMNc0pN7uAHIZ5EVdtIJO+XfkTHfvrLHHVBtLCOasoLDhGrJyrNpBGD/clflmFWN7c6cspJDCS8vOKqK+mDZWXVpKTlTcN0BlK+dmFNHb4BDLRsGLSutVb6NSRIDLRsKIv5n5LUSFxZKJhReu/2kpBp8LIRMOKhvZzpuyMPOrT05psTJxIUFlNQ/qOJhMNKwo+E0Fu7pOJx+NT337DqWs3I8rMzKVB5o4kJ6/LpKVLv6NDh46RnLwuBUxbROfOhZOcvC51VzMhB8dxtHjxN7R//xGxOuoa/Zi/g4OjKGDaInLVHcuksfruJOALacbwWeRu5Em8XB7NdZwvRjN92Az63HkBxQfG00/zNzL5X/isoJzkHBqr705j9d0pNzWPVk1YzZR3lN+1ThnpOeTi4k88Hp/69RtBysq9KTMzlywsRpOCgj6Tli37ng4dOk4KCvo0ffpiCgwMJwUFfRo61I2MjKxJQUGfLC2dSSCoZur07DmAFBT0SUnJkJ49e05ffrmWFJQMKCMzl0wH2RNblsOkxUu+pQMHjxFblkNTAhbQ2XNhxJblkOkge8rIzCXFrobU22QolZSUkay8LrFlOeTgOI6sbVwpOydfjNdYt8nUrVsv4vH4dOjQcdqx4wBlZuaSubkTycvrMUnkD8dJXl6PpjX5g7y8Hqmp9SFHx/G0ePG3tH//EbE6rVNaWhZ5jplCPVX7UmlpOVmaOZF2jwGUnZVPttZjSV3ZhEmrVqyjI3+cInVlE5o76wsKCYoSKw8PjaXQ4Gha+90WUlc2oRFD3Ckvt5B0Nc1Is3s/unr5Oo0e6kv80goaZelBfbStKS+7kFxsx5ORugWT1qzaRCePBJKRugUtnfs1RYTEkpG6BS2f/w2FB4v+7q87jCrLBWRn4UZjRvhRQV4x9dcdRsaaVpR09RaZD3LskBiupGhAkyfPp3NnQ+mff/6hAf3tSKmroaivDnIgWTkuk5Ys/ZYOHjpGsnJcCghYSOfOhZGsHJcGDXKgzMxc6trNiEz6DKMSXhnJK+iRgaEVlZaVk7JKb5KV41JgYDh9NucLkpXjkpf3dFJX6UOlvHKKibpEq7/8kbKz8miY1VhS62bMpJVfrKW//jhFat2Mac7M5RQcFClW3txGa77bwuSV8yvJxGgolfLKycLUsVP0KSrikdkge4bv0aNnSV5Bj0p4ZdSnr+0HX4Nqd2Oyd/ClRYu/pn37j4jVkZXjUu+elp/c74YNdKEKfhX14w4lI3ULigyJo1WL19Dre7z3TjfiQykjKY7cx7h8UL3X93jUXdmYSnl8GjTQntS796WsrDyysXIlla69mPTlF2vozz9OkkrXXjR75jI6HxRJKl17kZbGAFJTMSGVrr3IpNdQunv3PvP75InztGTRN6TStRepd+9Lehxz+q/v+9omSfcFnzr9F3pJVww+AizRF6BCAFwlot5ENADAdwAUAcwgooEAxgLYxWKxujdV+xnATiIyAVAHoP20chtYW1uglFcOPr8S9fX1CAqKgKenqxiNp4crTp4QfcgkJCQaDg6iWcbMzFzUVN8FAOTlFUFeXh5ycpJnEaytzVFa2iLnfFAkPDzFP1ri4emM0ydFckJDYhg5L1++QmOj6MNbCvLyoHc84FpaDUJZaQXK+VWor69HaHA0xnqMFqMZ6z4a506FAgAiQuNgJ2Gm7F2wsDIDv6wCFeVVqK9vQERwDFzdHMVoXN0dEXQmHAAQHRaPEaOGtuPj4+eGsPPR7fINe+lDvWcP3L6Z1k5WWHAMXN2c2shyQuAZ0apJVNgF2EmU5Y6w8zHMb6Wuipi3aAZ+23EQADDIciDK+ZWoLBegvr4BUaEX4OxmL8ZjtJs9Qs5GAgBiIy7BduQQAIBxXyPcvJYCAHh4vw5PHz+FmcUA6BlwweeVo+7BIwDAjYRkzJ83HTweH2VlFaivr8e5wHB4eYn7nZeXK46fCAIABAdHwdFxBADgxYuXuHEjBa/++aedfk+fPgMgmvmSk5NtfmBm0NeiD4R8IWoqatBQ34Cr4QmwdR0mRlNbdRdlBfx2H1kiIsjJy0FGTgaycrKQkWWj7v4jpryj/c6olwE0NHrg9evX4PH4TF8KDIyAZ5u+5OnpgpNNfSk4OBoODiLbZWbmovotfbbZdsOGWeHFi5e4e/e+qG3OhcHba4wYf28vVxw/HggAOH8+Ck6Odk35Y3DuXBhev34NPr8SPB4fQ2xEs3CJSbfxsO4R2iL+4jVYWpqBx+MjPj4BHI4mAgMjJPrDCcYfotv5wz//vHqr7Xr3NoSmpjpu3kiFpfUglJWWo7zJfiHno+Dm4SxG7+YxGmdOi1bQwkNjMdLBtlWZM8r5lSgsKGHy+vTtjbSUTCZW3biejBnzJqO8rKUvRYbEwcXNQUyOs5sDzp+JAADEhF/E8Ka+RAQoKSmAzWZDQUEe9fX1ePb0OXr3MUJGWjZeNcm5fSMNCxfO6pAY3rWrEpYunYuo6It4/bqe4X/uXJjkvtrsD8FRcGzyBy8v13b+YGNjAQCQYctAUVGko6KSIqqrawEAsbGXYdXURonXbkJLWwPB56Pg5inel9w9nHHmVDAAICw0FqNatZG7pzP4/EoU5Be38wVzi4Fi7d/R+hARlJWVAQCqKsqorq6FjY2FePz7gGtg4t+r9vEPAMwtTT+53wEAW0aUJ9JPAbU19yTKfxusLcygqqL8QXWaYdXm/iE4KBIebfqsu4czTp0U+UNoSAzsm/xB7P5BQZ4ZE5SVu2HECBscO3oOAFBfX4/Hj59+1PV1JN6AOjz9F5A+GHwcHAHUE9GB5gwiyiCiBCIqbvotBHAXQM+mBwknAEFN5EcB+L5LCIejhSqBkPktEFRDh6P1VprGxkY8efIU6upqYjS+vm7IyszF69evmbyDB7bj5q1ofP3NUuhwtFFVVc2UCQXV4OiIy9HhaDE0zXJ6NMmxtjbH7ZRY3EyOwRfLfmA6OhEhNPwoEpLCMGv2ZACANkcLQkFrWTXQbitLRxMCQYusp0+eokcP0fOVvoEuLiYGIyTqOIbaWonV+23fZlxKDMGK1QuhraMJoaCGKasW1kKrjZzWNCI5z6DWo7sYjde4sQgLjkFb+Pi5IyIklrne6layaoS10NHRbCerupWsJ2+V1fIQsvq7pTi07yhevhDdVGnpaKJGUNtKzl1otZGjpa2J6iaaFp1UUZBTjNFu9mCz2dDV52CgeX9oc7VQXlaJXiaG4OrpgM1mw9ndAXp6XFRWifsdl6MtJofD0UZV1b/7nSRERpxAVWU6nj57juDgKLEydW0N3BO2DGj3q+9DQ1v9nTwBIP9OATJvZuF06kmcTjuJtIQ7qCxp+epsR/odINoSFhYS02SXFjkCQTW43A+33bhx7shs02fDw48hLOwonj59huAmP6kSVIPTtm242kz7NTY24vHjJ1BXVwOHoy3WrlWCanDaXJskNF/vzJmTEBd3FQJBNTjt4tDH+QMATJrkg8BA0Y2Qjo4WhFUtfUkorGkX83R0tCBoG4t6qEFJSRHLVszD9q17xejz84phO8Iaaj26Q1FRAc6u9tA34KJa2NKXRPGhp1g9rTZ9tjk+xIRfxIsXr3ArNx5JGTE4vO8YHj96gqJ8HobYWqK7mioUFBXg4GwHQyO9Donha9euxO7df0BVVRX19fWt+NeAw9URq8tt5ZONjY14/KTJH7g64r5aVQMuRwdCYQ127joIXsltVJTfwZPHT3Hx4rVW9teGUFgL/8m+uHQxEUJBDXQkjBeCqlbx7vEz9FAXtdHyFfOxbcsetAURYfuO9TC3GIiZsyd1ij6fL1iN8LBjKOWlICDAD9u27wOXo4OqytZ9+P2v4V3Q1tH85H5XW3MPf+w7hqSMGNzKjcfTJ8+QdPXWO6/lU4HDaemPgMhe7fosR1u8zz5uuX+wsjbHrZQY3LgdjRXL16CxsRGGhnq4f/8h9h/YhsTr4dizdzOUlBQ7Taf/v0P6YPBxMAWQ9m8ELBZrCAA5iLYaqQN4RETN36yvAsB9S735LBYrlcVipb6h9rNsbWdZwWL9K03//ibYsPEbLF36HZP32WfLMWTIWLg4T8SI4Tawa5qR+Dc5LLSX07w8kJqaiaE2Y+EwyhcrVy2EfNP+RtfREzFqhDf8xn2GeZ9Px/ARNpIuF+2WGSTqBNTW3IXlQCc4jxyPdd9vxe9//IJuyl0BAIvmrYLDcG94u03DsOHWGDbC+t06vcN2FlZmePnyFYryS9rReY8fi/Dm2f138HkfWYOtzPDq5UsUNskaYNoXhkb6iI261IpHOxYS5EiiAYJOhaNGeBfBF4/hu40rkZ6ShcYGUYBet3ordh3eglMRhyGoEOLNm/ZnM7+fnHfPbnh6TYOBoTXk5eSYWeV3Xfv7gGOoAz1jPQQMmY6pNtNgPtwcpkNN/5X3p/C7ZviZ1SphAAAgAElEQVT6uSMkKOo92+jdfXbjxm+wZMm3YjTe3jOwePG36NKlCzOr/P783y33bWCxWBg0aCAaGhpwummm/kN1+jdMnOiNc+fC35uPRBoQvv5uGQ7s+xvPn78QKysu4mH3zsM4H3oE54L/RG52wVt8XPz3267F3HIg3jQ2wtbUFfZWHpi7aDr0DLjgFZfh4O6/cez87/j73D4U5Ba9V1/60Bg+aNAA9OptgIjwOIlx+X3b5m2+2r27Krw8XdGnry0MDK3Qtasipk4ZL3a5Q4dZ4ub1FNy6kfpBMr/5fhl+33ukXRsBgJvLZPy4dhsuX0rEnHkBsLMb2uH6LF82D94+M9Crtw2OHjuH7dvWfZI+/Fa8R4z7UL9TUVWGs5sD7K08YWvqCkUlRfhMdH/3tXwivC3eiNO0r9dsr7TUTAyzcYOj/Th8uXIB5OXlICMjA3OLgfjzj5MYOcIbz1+8lPju43+NztjW819A+mDQAWCxWDoAjgOYTaIvYEi8LZFUl4gOEZE1EVnXVD+GLpfDlHG5OszScjOEghqGhs1mQ0VFGQ8firYEcLjaOH3mIObN/RJlZRVMneYZi2fPnuPcuXBoafWErm7LjAiHq4PqmjZyhDUMTVs5zSgq5OH58xcYMED08mxNE4/79x4gMvwCrKzNUS2oFZt94XC1GbrW18fltshSVlFGXd0jvH5dj7qm7Q5ZGbngl1Wit7GRSFaTXZ4/e47gwEj01NQQmw3V4WjhrgQ5zTQiOd3wqO4xU+49XvI2ov4D+4DNZiM7M4/ho9NKljZHCzVtlnJb04js115WaKttRFY2FjAzH4CbGXEIiTmGXr0N8fny2dDmtszEaHM0cbeNnJrqu9BpommtU2NjI7as+RU+jgFYNGMllFW6gV8q8okrFxIxcewsTHL/DGUl5SguLoOerrjfCatrxeQIBDXQ1ZXsd+/CP//8g8ioeHi12VJxv/o+enJaZs80dDTwoPbBe/EcPmY4CtIL8OrFK7x68QqpV1LRf3A/pryj/A4QPcTJyMggKyO3yS4tcrhcHQiFbW1X/VbbcbnaOHv2EOa26bPNKC+vxLNnz5mtDbpcHWZbBMO/qpppPzabDVVVFTx8WAeBoFqsXXW5OmKzl2+DqWk/9O5tgFmzljE6VbeJQ/+m07/BzKw/ZGTYSE/PBiCKMxzdlr7E4Wi3j3nCGnDbxKK6h49gaW2OdT+txp3sy/h84Ux8sWoB5syfBgA4eTwITqPGwcstAHV1j8ErKhOb1RTFhzZ9qU2fbe5L3n5uSLh0Aw0NDXhwvw5ptzNgZjEAAHDuZCi8naZistccPKp7jMLCkk8ew4cMtcTgwWbIy0/C9z8sh6qqCmJizzTx10a1sEaMf5WgWix2q6qo4OHDRxBUVYv7qq42hNU1GO1kBz6/EvfvP0RDQwNCQ2MwrNUqmeNoO3TvroLvv93MXGPbviQU1ICr2yreqXZD3cNHsLI2x/oNXyEj5woWLJqFFSsXYG5TG9XU3IVQWAN19R6IioiHjY1Fh+qjodEDZoP6IyUlHQAQGBgOW1srEX+91n34/a/hXagR3v3kfjfCfiiqyoV4+KAODQ0NiIu8DCsb83dey6eCQNDSHwGRvWraxCShoE2fVRX12dYoKuTh+YuXGDCgLwSCaggENUhLzQQAhIXGwNx8YAdrIkUzpA8GH4dcAO33EwBgsVgqAKIA/EBEzet59wF0Z7FYzd+N0AUglFS/NdLSMtHb2BAGBrqQlZXFhAleiIqKF6OJio5HwDQ/AKLtBwkJNwAAqqoqCD5/BOvWbsOtWy2LG2w2m1nylJGRwVg3J1xLuIVevVvk+E3wRHTURTE50VGXMCVAJMd3nBsSEm4CAAwMdMFmswEAenocmPTphfKKKigpKaJbN9GsqpKSIpxG2yE/rwjpd7LRq7cB9A24kJWVhe94d8RFXxaTFRd9Gf5TRTutvHzHIOmayIzq6mrMSTYGhrro1dsA5fxKsNlsZsuHjIwMXMY64GbibRj1MoCePheysjLwGu+G+NirYnLiY65iwmRvAIC7jwtuJCYzZSwWCx4+rogIjm3XLj5+7ghvtb0o804OjHrpM7J8xrshPvZKG1lXMHGyDwDAw8cV1xNvi8ny9HEV43n8yFlYD3SCrcUYjHObgVIeHxNcZ8LQSA+6+hzIysrAw9cVl2Kvicm5HHsN4yZ5AgDGeo3GzSTRewUKivJQVFIAAAy3H4rGxkbwisoAAD00RP6goqqMqZ9NwM8/74GxsSEMDfUgKysL/4neiIwU97vIyHhMnzYBADB+vAeuXr3ezk6t0bWrErS1Rdue2Gw2xo5xQmGh+EpMYWYRuIYcaOlpQUZWBg7e9rgV/35L4veE9zBoqBm6sLuALcOG2TAzVLTaStQRfteM8RM8EBIk2haVmpoJY2MjGBiIbDdxooQ+G3URAU19afz4Nn02+AjWrt2GmzdTJdouPT0HhoZ6uHfvgaht/H0QEXlBjH9E5AVMny460cnPzwNXmtomIvIC/P19ICcnB0NDPRgbGyG56abobRjj6oBx49zx+PFTaGn1ZHSS5A/TGH9wx9WrN/6VbzP8/X2Y1QIASE/LRq9ehtBvikXj/DwQGy1+UlJs9GVMnjIOAODtOxaJTbHIa+xUWJo5wdLMCQd/P4pdvxzAn4dOAAA0NHoAEJ2G4+ntigO7/4ZhL32mL3mOG4OLbeLDpdgE+E32AgC4eTvjZqKoLwmrajB8pA0AQFFJARbWg1BazAcAqDf1JQ5XG2M8nfDrjgOfPIb/cfgEjHsPxYD+dnB08ENDQwMWfL6K8QeJfbXZH1r11cjI+Hb+kJKSgYpKIYYOHQxFRVG8cHS0Q0HTOxuzZ09Bv/4mePHiZVO8k8V4Pw+xlU0AiIm+hMlTRbPyPr5jkZgg6kseY6bCwtQRFqaOOLD/b+zccQB/HDrBjBd30rLR28QIY9xF8aEj9amrewxVFRWYmIge8kePHoWCghKmDzPx7wOu4V3ISs/95H4nrKqBhbUZFJr0Gz5qCEqaYntn4E5aFnq3un8YP8ET0W36bHT0JUwNEPmD7zg3XHvb/YOJEcorqnD37n0IBNUwbmobe4fhYu8N/W/BG6IOT/8J/os3nv9fTxCtANwGMK9Vng0AewCXAHwhoU4ggMlNfx8AsOhdcpQUDWic70wqKuIRj8endeu2kZKiAW3evIsmTJhDSooGpNa9D50/H0klJWWUkpIuOp1C0YDWr99Oz549p8zMXCYZ6FuShno/unMni7Kz8ig3t5D27f2LVLv1Jr9xs6m4qJRKeXz6cd12UlYyoq2bfyP/CXNJWcmINNT6UvD5KOKVlFFqSgaZDRhFykpGNG/OCsrLLaTMzFxKT8+myf7zSVnJiMwGjKKsrDzKysqjvNxChqemSl+a4jePSorLqKy0nDb/9CtpqvSlX7bupemTFpCmSl/S62lGYSExVMrj053UTLIZNJo0VfrS7GlLKT+viHKy8ikzI4em+YvoDbUtKCM9h3KzCyg/r4gO7T9KBuqDaMbEhcQrLiN+aQX9vOE30lMzpZ3bfqfPpiwhPTVTMta2pMjQOCrjlVN6ahaNsBjLnAQw0XMWpaVkSDwloLyskhyGeJGemilzetD0iQuIV1xGZaUVtHXDb8RVG0g7t+2nWVMWE1dtIPXSHkwRobGMLFuLMUzdCU2y2p5S1JyGDnKh/LwiMtGwormTl1FpCZ/KSytpx6Z9ZKJhRXu2H6LPA1aQiYYVDeTaUnRYPPFLKygzLYecrLzJRMOKHAZ7Eq+YTyWFpXT96i2yt/BgTjKKOB9LxQU8Ki7g0RdzvyU5eV3y9p7O+N2atT+TnLwubdy0k8aPn01y8rqkrNKbgoIiqKSkjJKT06lvv+HMiUNl/Ap68KCOnj59RpWVQhpk7ki6ehaUkpJBWVl5lJtbQPv2/UWKSgZiJw656o6l76evoUpeJQn4Qjry89/kqjuWTuw8SWtnryNX3bG0xGMZ3RXeo5fPX9Ljh4+JX8BnTjSKPB5F5UXlxC8sp6BD58X4doTfNSd+WQUNtxLJUFDQJx+flj67du02UlDQp02bdpGf32ekoKBPqqomYn22X78RpKCgT+vWifpsRkYOk/T0BpO+viWlpjbbrpAiIy9QUVEplZSU0Q9rthJblkMbNv5KPuNmEluWQ0rdjCgwKIKKi0spOfkOGfcZxpwy9MOarVRSUkYFhSXk4RnA5J8+E0JCYQ29fv2aKiuFNHfel8SW5VBxcSlVVgqIx+PTq1ev6PHjJ7R27c8kL69HmzbtpPHjPyN5eT1SUTGmoKBIxh/69RvBnDjEb+MPrU80Ki0tJzMzB5KX12NOFZrkN5dKikuptLScNv64g9SVTWj71j0U4P85qSubEEdjIIUGRxOPx6e01EyyNHMSO5VIXdmEft68mzmVSF3ZhG5cT6GC/GLKzsonX88ZZKRuQbMnLaHSEj7xSyto+8Y9ZKRuQb9tP0hzA5aTkboF9eUMoajQC1TGK6eMtGwaZelBRuoWNFDflqJCL1BhfgkVFfBo87pfmRNlkm+kUVEBj/KyCynAdz51RAxvfTJRv74jqJxfSUVFPCrhldGaNVtJVo5LGzfupHHjZ5GsHJe6KfeioKAIKm5qmz59bZlTctas2UolvDIqLCwhT69pTP6GDb9SQUEx5eTk04kTQdS1mxHJynGpvr6eSnnlVFZaTq9evaKHD+tow/odpNbNmLZt2UNT/OeTWjdj0lYfIGqjEj6lpmSQhamj2KlEat2Maeum35hTiSxMHSn7/2PvvMOjqNo+fD8pQCgBQUrogkjvRRCULiggoIgFe0FfFVCwi4JYwK6Iig1UUBCl9yZdkN6LSicEEOlNID7fH2c22U2WJmc3Id+5ufYie2b2/GZmz8ye8pSVa3XVyrW6besO3bt3X1jOp127B3XVqnW6YsUanTnz16S6WnnPv/9yDJs3p3j++UU0ClW7++jt/vrn75t0/do/dMSPY7V0XM0LiizU5bGH9Zo6V2u5smX12rp1dMiAT8/7s7HZSugtbR9I6j/06vmuxmYroX1699Xbbn1YY7OV0Ly5y+jIEeOT2kOl8vU1NlsJffjBrrp2rek/LF+2Su+47ZGkSEZ1a7fQpUtW6qpV63TsmClatFAVTeu+X8pX/pxlNNSvtDgv8TqqjgtERAoCH2JWDk4AW4AFwCuYFQUf96nqchEpgQlvmhtYBtylqsFDF3hky1o8LF9OpIRv4Sgm6sLiK/9XMkdGh0UnnFEDskZmCYvO1sPnNi+xRYO8Fc69kwWWHwrPDNqhk8fDogNwKvH0uXeyQFREZFh0smcKT/sGiM2U7dw7WWD3sf1h0YHwtYfsmcLjBHokjPdSuCicI++5d7LEhvXDw6JzefGm597JEgePbAxmlp1mFMhVNuQdgF0H1oX9nKPOvYsjGGqiDrUPsum1IGWo6iZMngOHw+FwOBwOxyVMRp1Ydz4GDofD4XA4HA6Hw60YOBwOh8PhcDgcF0JaJSALNW7FwOFwOBwOh8PhcLgVA4fD4XA4HA6H40JwPgYOh8PhcDgcDocjw+JWDNIxsZmyhkXn2OmzRk21SrjCBBbIlCssOocSwxdS77QmhkUnW3T4wkZuOrHn3DtZQCQ8Ed8iwqQTTiIjwjN/dOrf8LRvgGOnT4RF54tc9cKiA3Dv3hnn3skCOcP0u/RF9vAF8auU6/wyrF8sdx44GhYdCF8Y0b1bpp57pwxKmiUgCzFuxcDhcDgcDofD4XC4FQOHw+FwOBwOh+NCcD4GDofD4XA4HA6HI8PiVgwcDofD4XA4HI4LwOUxcDgcDofD4XA4HBkWt2LgcDgcDofD4XBcAM7HwJEmNGxcjzmLxvPr0kk88eRDqbZnyhRN/wHv8evSSYyfNpTCRQsmbStb/irGTvmBmfPH8Mu8UWTOnAmA6Oho3vmwJ3MXT2DOwnHc1LoZjZtcx+KlU1m24hee6vpIEJ1MDPy2L8tW/ML0GcMpWrQQANWqV2LOr2OZ8+tY5s4fR8tW1yd9JmfOHHw3uB+Llk5h4ZLJ1KxVFYBrG9Vh8vzhTFs4io6d7wt6Th9+2ZtpC0fx86RvKVQkzjvuKPr07cG4WT8yZsYQal1THYBs2bIyZsYPSa/f1k+n06uPBdRZq0FNvp/9DUPmfkeHx29PpVn56op8Pak/M7ZOoUGL6wK25SuYj/d+eItBMwcwaMYAChTOn/qL8uOahlczeu4Qxs4fxgNP3J1qe7XaVRg6ZSBLdsymScuGSeWly5fiu3FfMGLWYH765TuatW58Vp16DWszbt4wJi74mYc63ZNqe/XaVfhp6resiJ/H9S0bBWz7fMiHzP99Gp8Mfi9o3Y2bXMtvSyezePk0unTtmGp7pkyZ+PqbD1m8fBpTf/mZIl578FGocBzbEpbzROcHk8pic+bgm0Efs2DJJBYsnkTNWlUA++0BYPCoz5k8f3hSm7j88twBdTZsXI+5iyYw/yz31ecD3mf+0klMmDaUIinuq3FThjBr/lhmzBuddF/5aNq0PsuWT2flqpl06/a/oNfu2+/6sXLVTGbOGkXRooUBaNSoHnPnjWXhwknMnTeW+vXrpPrssJ++ZO26OSxbPp31a+fy7DOPB63/h+8/Y/3aufw6dyzFihVO2vbcs0+wfu1c1qyezfVN6yeVf/nFe+zcsYLly6YH1PXKy135488FrFo9i337N/Dnxt+snFP27NmYv2BC0mvrtqX0fqs7QFieRdVrVrHeBmJisjD4x/7MWTieWfPH8lKPrqnqjGtQiVZz3uGmee9R7olWqbb7KNKiJh12DiZ3pSvMsVyWncY/vUj7P76ixhuB97qvznC0h8qVyzNi8iBmLh7H+viF/LpyMo92eSDotfv4q7eZsWgsI6cMplARc+2ioqJ495PXmDjnZ6bOH8n/nkz+7JxlE5g452fGz/yR0dN/CHpd8jesRLM579D81/cofZbrV6hFLdolfM9llc31y3ddBRpPfp2mv/Sh8eTXyVu33Bk/C5C1XnWKT/iK4pMGcNlD7VNtj23TlBLzhlJ0xCcUHfEJse2aJ20rtXp8UnnBT3qeVadOw1oMn/M9I38dwr1PdEi1vWrtygye8jULts+gcYsGSeUFCudn0OSv+H7qAH6c+R233NM6aP3huJckKvNZzzEl3d98n+ta3E6bux69oM85wocbGPxHRKSAiAwVkY0islZEJohILRGZLyJrRGSliNzmt/8TIvKniKiIXH4+GhEREbz5bnc6tHuE+le3ok27G7mqdMmAfe64+xYOHjjENdWa88Wn39K9ZzcAIiMj6ffFWzzX9VUa1LmJW1rey6lTpwHo8vQj7P1rH/Vq3Mh1V7fi118X8977PWl38wPUqtGMW25tRekyVwbo3HPvrRw4cJCqlRvx6ScDefW15wBYt/Z3GlzbhmuvacUtbe7nw76vExkZCUCft19h2tTZ1Kx2PXVrt+T3DX8SERFBzz7P89Dtnbmhbjtatm3GlVddEaDVrkMbDh04RJNabRjY/3ueeaUzAO3vbgtAy/q3cd+tj/FCr6cQEY4ePcZNDe9Meu3ckcDsCXMCrmPXNzrz9F0vcHfDB2jSphHFSxUL0Nwdv4c3n3qbaaMCfwgBun/0HEM+G8bdDR6gY4vH2L/3wFm/sxd7P81jd3aj7XV30rxtE0pcVTxgn13xu3i5y+tMHBkY//nE8RN079SLm+vfxWN3dOWZXl3IEZv9jDov9XmGR+98kpuuvZ0b215PyRTXMSF+Ny91eY3xI6ak+vyATwfzwhM9z1j32+/1pP3ND1Gn5g3c0q4lpUsHtoe77mnHgQOHqFGlCZ99MpCevZ4J2P5mn5eYPnV2QFnvt7szfdpsaldvzrV1WrFhw8aQtAcf3R7tntQm9u7dF3B+vd99mTvbdeS6q1vRtl2LVPfVnXe348CBg9Sp1pzPP/2O7j2fBsx99ckXb/Ns157Ur9OKm/3uK1/d73/Qi7Zt7qN6tabceutNlElxL917X3sOHDhIpYoN6Pfx17z2+vMA/P33ftq1e5BatZrT8eFufPX1BwGfu6l1M44dPUZcXH7atrmPipUbctttbShbtlTAfg/cfwf79x+kTLl6fNj3S3q/+RIAZcuWon371lSq0ogWLTvwcd83ifByFHz33TBatEzdMQH4pN8AAKpVbULZMvWsnNORI0epU/vGpNf27fGMHTOZiIiIsDyLNv65OSRt4LN+A7i2VguaXHczNa+uSsGGlZLqkwih5pv3MqPD24xr8CzFW9cmtlRBUhKVLQtlHmzG3iV/JpUlnjjFynd+ZlmvwA6zf53haA993nyJvu98DsDLz7zBti07uOnm5lxZukTAfu3vasvBA4doWLMVX382mOd7PAnAja2bkilTJm64th2tGt3Bnfe2Sxo0ANzZ+iFaNLiN1o3vTKVNhFD1zfuY2+FtJtd/liJt6pDjqkKpdovKloUrH2rG337X7+S+w8y7512mNnqeRZ37U+vj1IPbZJ0I8r38OPEdu7OlVUdiWzQgU8miqXY7MnE2225+nG03P86hnyclleuJk0nlOx/veRaZCJ57syudOzzNrfXvplmbJlyR8rdix256dnmTySOnBZTv3f03D7T6Hx2aPsB9Nz7CvU904PL8eVLVH457SRNPnflaBqHNjU3p//7rF/SZ9Mq/qiF/pQVuYPAfENP7GAnMVNWSqloOeBGIAe5R1fJAc+BDEfFl2poHNAG2nq9O1eoV2bJpG9u27uDUqVOMHj6RZjcGzvw2v7ERw4aMAmDc6ClcW782APUb1WXd6t9Zu3oDAPv3H+Tff/8F4PYOben7wZeAWQq74oqibNq0lS1btnPq1ClG/DyOFi2aBOjc2KIJP3w/AoBRIydSv4GZ+Tt+/ASJiSYxUZYsmZOW1nLkyE7dujX57tthAJw6dYqDBw9TqVp5tm7Zzvat8Zw6dZrxo6bQ+IYGAVpNbqjPiB/HATBp7HTqXGsS3VxZugS/zl4IwL69+zl08DAVqwTO/BQrUYQ8l1/Git9WJZWVrVqG+C3xJGxL4PSp00wfPYN6za4J+NyuHbvZuG4T+m/gjVi8VDEioyJZPGeJOd9jJ/jnxJkTwlWoWo7tm3cQv20np0+dZtKoaTRodm3APju37+KPdRuTvg8fWzdtZ9vmHQD8tXsv+/bu57I8wRO1VaxmdHZs3cmpU6eZMGoqDZsHrnTs3J7A72v/RFPoAPw2ZzFHjxwLWnf1GpXYvGkrW33tYfh4bmgZuHpxY4smDP3BtIfRoyZxXYPk2e0bWzZhy5btrF/3R1JZjhzZueaamgz69ifAtIdDYWgPwahavRKb/e6rUcMnpLqvmt3YiGFDRgMwbvRk6nn3VYNGdVm7eoPffXUg4HusUaMKmzYm30s//zyWli2vD6i7ZYvr+X7wcABGjpxAgwamLa5YsYZdCSbh29q1v5M5c2YyZTKrEdmyZaVTp4cYP2EaJ0+eSqp/2LDR3NSqWUD9N7W6nkGDzHUePnw8jRrW88qbMWzYaE6ePMmWLdvZuHELtWqaVbw5c39j3/7gA97CRQqG5Jx8lCxZnLx58/DrvEVUr1E5LM+ikldeYb0NHD9+gnlzFiZprFq5lpi45JWqPFVLcnjLbo5s+4t/TyWydfQCijSrTkoqP9uOtZ+OI/Gf5A5X4vF/+Gvh7wFlKesMR3tQVSpULsvWzds5ceIfdiXsYezISTRNcc82vaEhw4eOAWDimKlcc12tpM9nzRpDZGQkWbJk5tTJ0xw5fCSVTjByVy3JkS27ObrtL/RUIttHL6BgkOtX/rl2/P7JOP7952RS2YHVWzmx25zPoQ07iMgcTUSm4JbUWSqV5tS2BE7t2AWnTnNowiyyNUq9enexlK9alu1b4on3fpemjJ5O/WaBCfESduziz3Ub+TfF79LpU6c5ddK0hUyZo5MGdP6E615CU/++nI0aVSqSMzbHBX3GEV7cwOC/0RA4par9fQWqulxVZ6nqH977ncAeIK/3fpmqbrkQkQJx+YmP35X0PmHnLgrE5Uu1z05vn8TERA4dOkzu3LkoeWUxFGXI8C+YMutnHutslmxjc5ob8rmXOjFl1s988c0HlCl7JfE7EpLqjI/fRVzBQHOZuIIFkvZJTEzk0MHD5M5zGWAeQAsWTeTX3ybwVJeXSUxMpHjxIuzdu49P+7/NnHlj+Ljfm2TNGkOBuHwkxO9OqnfXzt3kj8sboJW/QF52efskJiZy5NARLsudi/Wrf6fJDQ2IjIykcNGCVKhclrhCgcfZqm1zxo8KnInPW+By9uz8K+n9Xwl/cXmB81q0oUiJwhw5dJTXv+zJ15P781j3jkEfwj7yxeVl187k89uT8Feq8zsfKlQtS3R0NNu3xAfdnr9APhL8dHbv3EP+AheuE4y4uALExye3h53xu4iLS9ke8hO/w6/dHTxC7jyXkTVrDF2e6sjbvT8O2L+Y1x769X+LmXNH81G/N0LeHvr07cmYGT/weNdAM5G4uHxJ9wxAws7dqc8vLj8745Pb+2HvvipxZXEUGDL8S6bMGs7jfqZSAAUL5mdH/M6k9/HxCanuJf99fPdsHu9e8tGmzQ2sXLGGkydN5+aVV7rRt+9X5MyZ0/wYe+yIT6BgwQKB9RcqwPYdyfUfPHiIPHkuo2DB5PKkzxYK/Gww2rVrRbXqlfis/9vkyhVr7Zx83Nr+Job/PC6pnnA8i4oXLxyyNgDmOXt984bsnrsmqSymwGUc25m8cnUsYR8xcYHX6LIKxchaMDfx05anqjMYKesMdXvo+nQP7nukA9WvrsKLvbrxzmt92bVzDwVSXLv8cflI2Jn8fDjs3bMTx0zj2LHj/LZ2GvNWTObLT77l4IFDAKjCdz/3Z8z0Idxxzy1BzjU3x+OTMxQfT9hHTIHA65erQjFiCuYhYdqyM55DoU4OSCEAACAASURBVBa1OLB6K/+ePB10e1S+PJzelfx7cXr3XqJTzMYDZL++HsVGfUbchy8R5fd7IpkzUfSnvhQZ+gHZGp95QJGvQF52xydnft+T8Bf5zvN3CSB/wXwMmf4N45cM59t+37N3d2D25nDdS5Dxsr2fLxqGf2mBGxj8NyoAS862g4jUAjIBGy+kYhHpKCKLRWTxqcTU6dNTNhN/04mkfVSJjIyiVu1qPP7ws7Rufhc3tGxCvetqExUZSaHCcSz6bRnX12/HkkXLueOOtkHqSKmT+lh9swhLFq+gds0baFi/LV27PUrmzJmIioqicpXyfP3V91xb9yaOHjvOU90eDVpRSgeeM53Tzz+MYdfO3YycNoiXXu/G0kUrOH06MWC/Fm2vZ9yISYEfDvbcOs8lusioSCrVqsAnr31OxxsfI65oHDe0b3bG/c92nc6Xy/Pl4Y2PX+GVJ98482eD6Vh6iJzPOZzpO3r+pc581m8gR48GrkZERUVSuUp5Bn71Aw3qtebY0eM82fWRkLWHbo92p2X927ij5UPUqF2VW29vffb6OB9NiIqM5Ora1Xj84Wdo3bxD0n11rmNNUflZ9ylbthSvvf48nTq9CEClSuUoUbIYY8dMRoJ88ed3vc7z2FLQ//Pv6Nr1FcaMmcyuXXvo3ae7lXPyp127Vgz7acxZj/0cUhf8LGresknqOiy1gcjISPp/9S5ffT6YI9v+Omt9AZIiVO95F0tfDW5fH4zz+U5ttodHOt7DiKFjGDdiEq+/9A59+va8AE2lcrUKJCYmUrt8U66rdiMPPX4PRYoZc6B2N95Lq0a3c/9tj3P3g7dxee0yKU42yAH564pQ+dW7WNnz+zMef+xVhajY/XaWPvv1mU/yPK7LkZkL2Nz4Xra2+R/H5i+jQO+nk7ZtanQ3227tzK6n3yLfC48S7flEpdY5++mci90793BH4/toU+d2WrZvTu7LAwdJ4bqXIrIGX9V2XLq4gUEIEJE4YBBwv+qFrbOp6heqWkNVa/y95wiF/GZw4goWYHfCnoD9E3buSprliYyMJDY2B/v3HyRh5y7mz1vEvn0HOH78BL9MnU3FyuXYt+8Ax44eY8JYY7M4dtRkChWOo1Dh5IdXoUIF2JWwO0BnZ/yupH0iIyOJzZmD/fsCl5p/37CRo8eOU65caeLjE4iP38WSxSsAGD1qIpUrl2fXzt0Bs7oFCuZnz669AfXsSthDAW+fyMhIssdm58D+gyQmJvLmy+9zU8M7+d893YiNzcHWTduSPlemfCkioyJZs3J9QH1/JewlX8HkWei8cXlTza6ciT0Jf/HH6j9J2JZAYuK/zJ08j6sqljrj/rt3/kUBv1mZfHF5U53f2ciWPSv9Br9Lv7e+YNXSNWfcb3fCnoDZn/wF812QztnYuXMXhQolt4eChQqwa1dguzPtwa/d5czO/n0HqF6jMj1fe5blq2fw6GP38VS3R3mo413sjN/FTv/2MHoSlaqErj3s9mb8jh49xtgRk6haraLf+e0OmBmNK5g/ydzF/xoULJTc3nPE5mD//gPs3Lk74L6aPnU2lSonmy/Fx++icKFkm+lCheJS1+23j++e3efdSwULFWDI0M95+KGubN5szqXW1dWoWrUia9fN5aXuXciZM5aJk4YCULhQHAkp7tX4HQkUKZxcf86csezbt5/4+OTypM/uDPxsSvbs2cuO7QkULhTHwAFDqVG9spVz8lGxYlmioiJZvmx10vULx7OoQP58IWsD7370Kps2beXLz74LqO9Ywj6yFkw2Lcoal5vju/YnvY/OnoWcZQrTZPhLtP7tAy6vVpL633RNckAORso6Q90e7rn7ViaOmUZcoQKMHz2FytUqUKBgPnaneD7s2rmbuILJz4cc3j3but0NzP7lV06fPs3fe/ex+LflVKpSHoA93j379959TB7/C7mrBPotHE/YR0yh5Jn7mLjcHN+d/L1HZc9CbJki1B/RnRsWfkjualdyzTfdkhyQY+JyU2fAUyzq3J+jWwOP15/Tu/cS5bf6GpX/ck7v2Rewz78HDqPeyt3BnyaRuXzyb0LiX2bfUzt2cWzhSjKXDfRd8bEn4S/yF0q2AMgXl5e/dl/4M3zv7r/ZuGELVa+uHFAernvpQp2PMxLOx8DhzxogtXEjICKxwHigu6ouuBiR5UtXc0XJYhQpVojo6Gha33IDkyfOCNhn8sQZtL+jDQAtW1/P3Nm/ATBz+jzKlS9NTEwWIiMjqV23Jr9vMM5YUybN5BrPTrte/dqsWL6GkiWLU6xYYaKjo7m5XUsmTAh0wp0wYTp3drgZgDZtb2D2rPkAFCtWOMkpqUiRgpQqdQVbt+1gz569xMcncGUp81Cu3+AaNqz/k1XL1lL8iiIULlqQ6OgoWrS5numTZgVoTZ80i5tvawlA81aNWTB3EQBZYrIQkzULAHXrX01iYiJ//r456XMtb27OuBGTU13H9cvXU/iKQsQVKUBUdBSNWzdk7pRfz+s7WL98Azly5SBX7pwAVKtblS2/n9lNZM3ydRQtUZhCReOIio6ieZsmzJoy97y0oqKj+GBgH8b+NJGpY2ecdd/Vy9ZRtEQRChWNIzo6ihvbNGXG5Nln/cz5snTJKkqULE5RX3u4pQWTxge2h4kTpnP7naY9tG7TnDmzTFNv0exOqlRoSJUKDen/6Td88F5/vvpicOr2UL9OyNpDZGQkl+U2s1hRUVE0vL5egL/D8qWrKFGyGEW9+6rNLTcyJcV9NWXiDNrfYVYZWrZuxrzZ5vxmTp9LWb/7qk7dmvy+IXlRcMmSFZS8MvleateuFePHB5q2jZ8wlQ53GVOJtm1vZNYs0xZz5oxlxPCB9HjlbRYsSF6Q/OrLwVxZ8mrKla1Hwwa3cPr0aR595Gmio6Np3741Y8cFOpePHTeFu+++FYBbbmnBjJnzksrbt29NpkyZKF68CFdeeQULF53Z5AKgQIF8Sed07723sXbdH1bOycett97ETz+NTXq/dMnKsDyLFi9aFpI28NxLXcgRm4OXn++d6lz/Xr6JHFcUIFuRvERER1KsdW12TFmatP3U4eMMr/A/Rl/9FKOvfoq9Szcy67732bdyc6q6gtUZjvawM2E3WWKyULxEUVq3u5Gtm7bRqm1zpk0MvGenTZrJLbffBMANNzVlvud7Eb9jV5KPUEzWGKrWqMjGPzYTkzWGbNmzJpVf27AOBzfsCKhz//JNZL+iAFmL5EWiIynSujYJk5Pb1OnDxxlb/lEm1nqSibWeZN/SP/n1vvfYv2Iz0bFZqTvoaVb3/pG/F/1+1nM8sWoD0cUKElUoP0RHEXtjfY7OCPwpj8ybPBjL3qg2J70JiYjY7Eh0tPk7Vywx1cpxcmPgYNjH2uXrKXJFYQoWMb8V17duzOzJ5/dbkS8uL5mzGF+dHDmzU7lmRbak0AnXvaSnA00D/z+hqiF/pQWSUeOwhhLP+XgB8JWqfumV1QSyAq8AY1X1wzN8dgtQQ1XPOTUQl6ucNmp6Hb16P09kZARDB4/ko/c+55kXn2DFsjVMmTiDzJkz8fHnb1GhUlkO7D/Aow88zbat5oF6S/tWdHrqYVSV6VNn83oPE5qycJGCfPx5H2Jz5uDvvft59JGnKVuuNH3e6k5kZASDB/3Mu+98yovdn2TZ0lVMnDCdzJkz8cVX71GpUnn27z/AA/d1YcuW7dx2exue6vYIp06dRv/9l7f69GP8ONNpqFixLB9/0pvoTNFs2bydx//3LJn+iaB+k7q89Ho3IiMi+XnIaD77YABdnnuUVcvX8svk2WTKnIl3P32NchVLc2D/QZ7q+CLbt8ZTqEgcA4b1Q/9VdiXs4cUne7FzR7Kd8C+LRvPQHV3Y9OcWCmQKXN6s3agWnV99nIiICMb/OJFBfX/gwafvY/2KDcybOp8ylUvzxtevkiNndk7+c4p9e/ZxTyNjO1zj2uo88cqjIPD7qj94+9n3Oe1FITmUeDzV91avcR2e7dWFiMhIRg0Zx1cffctjzz7EmuXrmTVlLuWrlOWDAb2JzZWDf06c5O+//ubm+nfR4pZmvPrhS2zcsCmprle6vMGGNaZTe1oDzaaubXwNz7/2FBGREYwcMpYvPvyGJ57tyJoV65gxeQ4VqpTlo4FvE5srBydPnGTvnr9pXf8OAL4b/TlXXFmMrNliOLD/EK889TrzZppBZcKxfTS5vj5vvvUSkRGRfD/oZ95/9zNeeKkLy5atYtKEX8icORP9v3yXipXKsX//AR66/ym2btkecHzPvdCJo0eP0a+vWbavULEsH/V7g0yZotmyZTtP/O95ok5gvT3EZM3CD2O+IioqisjICH6dvZAXnn89wEm4cdPr6NX7BSIjIxgyeAQfvfc5z77YieXLVifdV/2S7quDPPJAt4D7qvNTHZPuq9d6vJtU7+GTx2nWrAFvvf0KkZGRfPfdMN55+xO6v/wUS5euYsL4aWTOnJmvvn6fypXNvXTvPZ3YsmU7zz73BE8//RgbN25Jqu+mVnfz11/Jq1tFixZm8uSh/HPyJBEREXzz7Y/07tOXnj2eZvGSFYwbN5XMmTPz7Td9qeLVf+ddjyXN1L/wfGfuu/c2Ticm0q1bDyZNNp3hwYM+of51dbj88tzs3r2XV3u9y8BvhvLNwL5UrVyebNmzcvnlefj77/0MHDjE2jmtXjObm9vez++/byQqwnREml7fIOTPom5PdKdGrSpW20BcwfwsWzuT3zdsTPKjOPLtPDb+MDPp3As2qkz1V+9CIiPYOHQWa/qOodIzt/D3is3E+w0SAJr8/BJLe/2QNDBo/dsHRGePISJTFKcOHmP6HX049MfOpDr/4p+Qt4e619Sk34dvkjNXLPkK5GX/vgN8P3AYn7z/FU89/xirlq9h2qRZZMqciQ8+e4NyFctw8MAhOj30LNu3xpM1WwzvfNyLK0uXRAR+/mE0X/T7liLFCvH5dyZiVWRUFGOGT6B4v9TzagUaVaZyr7uRyAi2DJ3F+o9GU+6ZW9i/YjMJKa5f/eEvsbLXD+xfsZkyT7ahTKdWHNmUPGM+5/Y+/PO38W+olCtwBTnbdTXJ+8IjEBHBoRFT2Pf5UPJ0upsTq//g6IwFXP7U/WRrVBtOJ5J48DC7X/2YU5t3kKVKWfK/2hn+VYgQ9n83ikPDkyer7jwQaB5ct1FtuvbqTGRkBGOGjmfAR4N45JkHWbdiPbOnzKNc5TK8M+ANv9+KfdzW4B6uvq4GT/Z4AlVFRBg2cDgjB48NqPuPwzvDci81u6bUBTkgP9OjD4uWreTAgUPkyZ2Lxx68m1tandk815/oy0ukK4eGLFmKhrwDfeLEtrCfsxsY/EdEpCDwIWbl4ASwBTNYeAWzouDjPlVdLiKdgWeBAhin5Amqmjp4th9xucqF5cs5dvrMUXZsky8mPPaIKQcGoSLYwCBUpBwYhIqEY/vOvZMl8mSJDYvO4VPBIzBZ1zkZvvbwz+kLCxP4X8kcFR0WHd/AIBzERGU6904WeC9r0IXlkHDv3rOvMtqiSI7zd5C9GN7JVCEsOpB6YBAqUg4MQskfh3eeeycL7N0y9dw7WSK9DQwyZykS8j7aPye2h/2cXebj/4gXdSh15hN47Qz79wX6hvSgHA6Hw+FwOByO/4gbGDgcDofD4XA4HBdARrW4cc7HDofD4XA4HA6Hw60YOBwOh8PhcDgcF4JbMXA4HA6Hw+FwOBwZFrdi4HA4HA6Hw+FwXAAZc73ArRg4HA6Hw+FwOBwOCE/mNvcK7wvo6HTSt5Y7p/SvkxHPyV27S0Mro+lkxHNy1+7S0XKvC3u5FYOMSUenk+613Dmlf51wamU0nXBquXNK/zrh1MpoOuHUyojn5LhA3MDA4XA4HA6Hw+FwuIGBw+FwOBwOh8PhcAODjMoXTifda7lzSv864dTKaDrh1HLnlP51wqmV0XTCqZURz8lxgYjnBOJwOBwOh8PhcDj+H+NWDBwOh8PhcDgcDocbGDgcDofD4XA4HA43MHA4HA6Hw+FwOBy4gUGGQEQiRWRaWh+HbUQkm4hEeH9fJSI3iUh0Wh+XI23w2nlBESnqe1muv4LN+tITIlJNRDqLSCcRqZbWx2MDEaknIvd7f+cVkSvS+pgcDofjUsc5H2cQRGQMcLeqHkwD7aaqOjUE9S4BrgUuAxYAi4FjqtrBUv1dz7ZdVd+3oeOnlxd4GCgORPnpPGBTx9MaDgwAJqrqvyGo/zBwxoeHqsZa1usE9AB2A77zUVWtZFFjLpAJ+Ab4QVUP2Ko7hc5ZO+aqutSy3ivArcAIr6gN8JOqvm5Rw789iPe/en9rCNpDD6AGUFpVrxKRgphzqmtTx9PKCnQDiqrqwyJSytMdZ1vL0/tdVa8KQb2VVHWl93c08BxQC1gNvK6qxyzpPAEMVdW9InIl5jlUCdgAPKSqq2zoeFojMO16lKoesVVvEJ0SQHdgJ9AH+ACoA6wDnlHVLZZ0IoD7gFuAwsBp4A+gv6rOtKHhpxUFPAi0BQpi7tedwGjga1U9ZVPvDMfwhaq6RGfpDDcwyCCIyDCgNjAVOOorV9XOYdDepqpWZ2+9epeqajWvUxijqm+LyDJVrWqp/h7en6WBmsAY730rYLaqPmRDx0/vV2AOsARI9JWr6nCbOp5WE+B+TJv4CfhGVdeHQKcXsAsYhOkEdgByqOrblnX+BK5W1b9t1htEpxTwAKYjvRAYaHvQKyIzvD+zYDq3KzDXrhLwm6rWs6y3Dqiqqie89zHAUlUta1MnnIjIcqAq5jyqemUrbQ4U/bR+xNyz96hqBe/6zVfVKhbqDjagygocw/KAyvc89f5+D8gDDMQMFPOo6j2WdNaoannv7/HAV6o6UkQaAG/YHLyJSDwwH2gETAOGAONV9aQtDU9ntld3TuAuzHUbBlwPdFDVRpZ0BgJbMefSDjiE+c14Dhitqh/b0PG0hgAHgG+BHV5xYeBeILeq3mZJJ/eZNgErVLWwDR2HPaLOvYvjEmG89woJ3opE0E2YH5gQyUodTGfzQa/MWptV1Vc9kSlANVU97L3vielM2yarqj4XgnpToarTgGkikhO4A5gqItuBL4HBFmeDmqnq1X7vPxOR3wCrAwNgOxDy1TBV/UNEumNWp/oCVUVEgBdVdcTZP33eGg0BRGQo0NE3g+qZMj1tQyMFWzCDkBPe+8zAxhDoAMbEByilqgNF5HLMQHGzZZmTqqoiop5mNsv1+1NSVW8TkTsAVPW41yZs8A2ms/mMqu4GEJHNqhoKsyj/Y24M1FTVU16nd4VFHf9ndD5VHQmgqjNFJIdFHYA9qtrOq7cNZkX2CxEZBwxR1SmWdHKo6mcAIvKYqr7nlX/trZDYorqq3u/9PVdEFqjqK953tBywNjDA/OaVTlG2A1ggIr9b1PkLM9jxb3++1cR8FnUclnADgwyCqn4bYolrMTMlKZdrBbMcHQqeBF4ARqrqGm85d8Y5PvNfKAr4zzCdxJj72GaciNyoqhNCUHcqRCQP5ju7G1gGfA/Uw8wINbAkkygiHYChmIf9HfithlhkEzDTm4H8x1do09xLRCphVllaYFbeWqnqUs9MZT7Jpji2KONvVqGqq0Xkomehg/APsEZEpmK+o6aYTkdfT9faqqK/iQ9mVjUTMBiwbeIzTEQ+B3KJyMOYVZ4vLWv4OOmtEvgGISXxa4MXg6p2EpHqwBARGQX04ywmehdJThFpi/EtzOybHPAfYFniZxH5BugFjBSRJzH3TmNgm0Ud8K6VN6kzCBjkzVC3B54HbA0M/hWRqzCDuKwiUkNVF3umUpGWNABOiUhJVd3omRyeBFDVfyx/RwD7ReRWYLjP3NQzZboV2G9RZxPQWFVTfffeZJUjneEGBhkEEdlMkB8UVS1hSWIBxr5/VhDtDZY0AvC0ZolIDhHJrqqbgFCYRg0CForISMw1bAt8FwKdLsCLIvIPcIoQ2V9Dku1tGcy5tVLVBG/TjyKy2KLUncBH3kuBeV6ZbbZ5r0zeKxT0w3QuX1TV475CVd3prSLYZp2IfIXpOCtmELcuBDojvZePmSHQ8NEWz8QHkq6d7VliVPVdEWmKMbW4CnglFH5OHj2ASUAREfkeM8i5z1blqrrEM/17ApiFWd0JBbOAm7y/F4hIflXdLSIFgL22RFT1JRG5D2N6UxKzQtURGIVZ/bVJKr8CVd0H9PdetngWGIvxb2oDvCAilYFYzCqFLZ4BZojICSAauB2S/NNs+7TcDrwFfCoivoFALszk2+0WdT7E+AkGGxTaXll2WMD5GGQQvNlhH1kwo/7cqvqKpfpLYZaF56UovxbYqarWTRNEpCKmg54b04n+C2PnuyYEWtUwqyJg/AuW2dYIF96sT3dV7ZXWx3KpICKRwHe2HNvPUzML8D/gOq9oNvCZzxfgUkREFqpqLT//oGwYe/xQ2P4XwKxWKrBIVXfZ1vDTyoPx1xFggapa60in0InD+IOEZVXR8d/xzOT2q6rVFVLPTC1PqNrYGTTzYPqDYdN0pF/cwCADIyJzbTkyejabL/qiWviV1wB6qGorGzop6v4VeElVZ3jvGwBvquo1luqPVdVDZ3KO8maebOiUUdX1coZoNGo5Co2nOV9V69iu16/+Zz1n8I8JvlJlZWVHRD5U1SdFZOwZdG4K8rH/qjUJuMm242JaISLDVLW9iKwi+LULRWf9aaAUxlypN8bE5webTpOezkPAK8AvmM56faCXqg6wqeOndzPGDE+BuT67+VAiIYr2lpZa7pzSl46IxAJ5U07siV8Eq0tJx2EHNzDIIKTodEZg7Hz/p6qVLdW/WlWDxnkXkVWqWtGGTop6V6Q8/mBlF1H/OFVtGcQMy2fiY8UMS7yQbJIcjcYftRXRIoXmq8BKYISG4CYXkVaqOlZE7g223ZbPi4hU90wt6p9BJ5Vp20VofQ5Uw0Sn8o/sZTtsbVg67CISp6oJIlIs2HZV3WpDJ4huU0y0FgEmh6LT5JkvXqNelCpvxvPXIM6UNrQ+Ba7EmMYA3AZsVNXHbWul0A1JtLe01HLnlH50RKQ9xsxnD8Zs6T5VXeRtS4pgdanoOOzhfAwyDu/5/X0aE4mkvcX6z2b3GmNRx59NIvIyxk4ejA22tegmqtrS+/+sEUBEpPzFmC+pF6dZvWg0YaIrkA3jHHwcy/4MqjrW+/+sAwAR+VhVO12EzhLvf2sDgLOw03tFANbt4v3o4v3fMoQa+PxKzjUAsL265A0EQj2DugM47Pf+MCZyVSioD1TwDbBF5FvASix+CWO0t3BpuXNK/zoeL2KiICWISC2M47Yv+pqtqFvh1HFYwg0MMghh6HQuEpGHVTUg8oeIPIiJ8R0KHgBexUS0EIwN9v1n/URoGISZSb5oxISkLIffQEtVrTs6q2ooO7YXgpVoNJ6PS29SXztbzvX+4WtzmLehSZiUVh32s3DRzq4S5oR3QDzwm4iM9nRbYwIIdPX0bK7ybMBELvN9X0Uwq3E2CGe0t3BpuXNK/zoAUX7PooUi0hATOa8wdiNjhUvHYQk3MMggiIlX34NkR8ZZGJtbW7Hfn8SEnutA8kCgBiZCTFtLGgGo6n6gs3du/6qXZyANsDKrISaUYwNM53YCcAMwl9BEQEJEbiK5PczUEGVqDRMDMe37A6AhZoBodbbJG7QNwji7IyJ7CZGz+3kSqug0KbnoH2ffQFTOkPDuYusPwkYCczGM9v4PhVYeTASphd77msB83+zuRfq5hDPaW7i03Dmlfx2AQ+KFRgUzYeH58Y0Eyl+COg5LOB+DDIKIDMektveZdtwNVFbVmy3rNAR8vgZrVPUXm/Wn0KoJDCD5x/4g8IDPvCRc2LKD9GzKKwPLVLWyiOTHZAUNheN2H0wH5nuv6A5giao+b1vrHMdh69otUdXq/v4sIjJHVa8912cvQCOkzu7/4XjCYn9r2Z74Nw1MeBe0zIJOBVVdbbPOs2gF9W/xcTFmbhLGaG/h0nLnlP51vDprAllUdU6K8uuA61T19UtJx2GPiLQ+AIc1SqpqD1Xd5L1eBayZWfhQ1Rmq+rH3CtmgwONr4DFVLa6qxYHHMTPHlyrH1SSSOe1FadhDCL4jjxuBpqo6QE2kluZeWbixNat/QkwY1j9E5AkxiZpsZ83M5hsUgMnUivHTyOjYXHlJFJEOIhIpIhHeCmMoEt71F5GFIvKYiOQKQf3+VARWquqsYK+LrPsDAn0lfBzHOGzaJFxa7pzSvw6YFdhgFgXHAJsD+XDpOCzhBgYZh+MikhSaVETqYh4mlzKH/WcZVHUuwR+aocZW+MrFXifmS4w51lJg4dk/clH4d5hyhlAHEYmV4ImsPrIk8SSQFZPgrjpmRSxoRKSLYJOIvCwixb1Xdyw6u/8HrHXYRaSYmCRaiEhMiu/qbls6mOR27YHdmIHvrYQg4Z2aMMx3Yez9F4vIDyJyvW0djwIYH6thItJcRGwOpIprkHCNqroY+9nXw6Xlzin964RTK5zn5LCAMyXKIIhIFYwZka8DuB+4N9gNeakgIh9gOoNDMHbQt2HOazjYi//v/dB3AEqoai8RKQoUUNWQddpFpDgQG6rvR0TuAPpgslgKxtfgBVUdalmnBmYVJ4enc4A0MPeygYhchnF2r0eys3tPz9clVJrFgFKqOk1EYjCOeoe9bVbMZUTkYUzm2dyqWtIzV+ivqo0vtu60RkxiujZAX0wWZMHkWxlhWUcwIVjvx/hWDQO+vljTDhH5U1WvvNBt6VnLnVP61wmnVjjPyWEHt2KQcViHSS8+ABPFZxTmB/NSpgpwFWYpsidQFrgGE5r1XYs6nwJ1MHb4YFYlPrFYfxIiUslzCq4GXCkmcZJ1VHUIJlPrCO9Vx/agwGMAyeZexQiRuZeI1BCRkSKyVERW+l42NVR1v6p2VtVqqlpVVbuEeFDwMPAz8LlXVBhz3/qOx5YN/eOY6FCHvHr/wL4ZWLPfmQAAGVBJREFUFgAiUtj7nvaIyG4RGS4m+ohtnUrexME6oBHQSlXLen9/YFtPzQzaLu91GrgM+FlE3r7Iqhd57SAACU20t3BpuXNK/zrh1ArnOTks4FYMMghisrYewJinJNn0qup7Z/zQJY6I3KsWEmn5nC9FZJmqVvXKrCVS89MZAFQC1gD/esWqqg/Y1PG0gjmTHgS2quppizrzVLXuucos6GwAnsHEj/ddO6tJuiR4duWDwGLgc1U9YUvL01uOCUH4m1+7s54sUDznX1/7FpEoYKmGJvPxVOAHAnOPdFDVppZ1ZmNM8n5W1eMptt2tqoOCf/I/aXXGmK3tBb4CRqnqKZ/Pi6qWvIi682Ois5wkSLQ3Vd11UQefBlrunNK/Tji1wnlODju4gUEGQc6SmTijIvYi3vyGWYlY5A0Q8gJTfJ01W4jIWlUtZ7POs2gtwKxKrMSYV1Tw/s4DPKqqUyzphMvca65nVx4yROQjIC+BGW53YRL4xaqqTVv8sHXYvVntA8A9QCfgMWCtqr5kU8fTWq6qVc5VZkHnSVX9MEVZF1W15dPiX28vjNlQqkGoiJRV1XUWNMIZ7S0sWu6c0r9OOLXCeU6Oi8MNDDIIIvIF8LGqWsnIeSngP8N/kfV0wHQCq2H8NNoBL6vqsIutO4XO18B7qrrWZr1n0BoKvKZeDH4RKYeZcX8NGGGroyYiM86yWVW1kSWdxhhTr+nAP34C1mzJRWS2ql4XrExE1qiq1Zjb4eqwezPbD2Js5AWYjAmTa/3hLyLTgG9IHlzdAdxv258h2KSAredBEK1BKQeFwcocDocjI+AGBpc4YmLjKyZZXSlgE6bjJJiOmXVzgfSCrRUDr64yQGPMdZtuYxYwiMZ1wFjMLHRIv6OzzdyGYgY31IjIYKAMITTDEpF1QDNV3ea9LwpMUtVyoeh0hqvDLiLZgBOqmui9jwQyq+oxmzpe3UWBfhifHQV+BbrYMvkS41R/J8ZB3D8ueg4gUVWb2NBJoRnwnPGu36pwrf45HA5HOHGZjy99Wqb1AaQhtjIS+2b/1gcps8kATGjIADv5ELFBRD4DfA7HtwG/i0hm4JQtERHJg3EOr4fpCM7FZNz+25aGR2XbtvdB6AbMFZGNmLZ1BfCY17G+aF+WIMQAA1T1S0jqcMZg4nvbZDrQBDjipzsFYz5nFW9QdTGZgM/Fr0ACcDkmCIGPwxhTOWuIyAvAi0CMiBzyFWNspb+wqeVwOBzpBbdi4EiXeLOp7c5mziMi/VT1CQtaYZkRFJFfbJnWnIdWDMY0xRd6cy4m+tIJIKuqHjnLxy9EZyomrOdgr6gD0MD2zK2IfAl8EGozLG/gVAZzzdbbdjhOobUAaOL7LkQkO8a3xWqHPVx2/169V2DMoorjN/GkqqEcLAQ7jvmqWsdSXb1V9YWzbC/vM9lzOByOSx03MHCkW4LZfFuuP2lGEDNL61uBOAl8cbbOwH/U+xSTdGwsIbKTT6EXAxRV1Q2hqN/TWKKq1VOULVbVGpZ11gElMQnHQmKGJSJZga5AMVV9WEy8/9KqOs6WRgq9cDnqzgM6+RzBRaQ60M9WxzmF1gpMxvKU0aMuNkPwhR5HSPwNzqBlzaTR4XA40hpnSuRIz0wVkaeBH4GjvkJV3WejclXtDfQ+14ygRWIwnVr/DK2KyTNgFTG5Et7BhIS7QkwCvF4hmLmdISK3YxI+gXHcHm9ZA6B5COpMyUBMOD1fh3kH8BMQkoEBcFREqqXosIciW/mTwE8istN7H4cxLQsFJ1S1b4jqvhDCOeNlMxOyw+FwpCluxcCRbhGRzUGKVVVLWKq/jKqul+Ax/62F2kwLRGQJJtnTTE2Okb8yBKEwDwPZSM6dEUnyIE5VNdaiVmXgWu/tHFVdYatur/7FqlpDQpzPwk+vJsYHJKDDriHIGi0i0UBpkk2krPmZpNC5ExMEYQqBq2JhvZfCOYvvVgwcDkdGwq0YONItqnpFiCW6Ah0JdGL0Hylb9QcQkwH2Y0wWWp+jbhdV3WFTx+O0qh4UCe1kpqrmEJHcmM5gFr9yq6YjItIFeJjk1ZXBIvKFqn5sUeakZ36lnmZJ/Dq3tlHVRV40rJB02EWkkar+Iqmza5cSkVCZsFXEONg3wi96FJbvpfPAzeI7HA7Hf8ANDBzpFj+b76Kq2tG2zbeqdvT+/AwTlvKQiLyMyWfwmg2NFAzEZIW91Xt/l1dmNSusx2pv9jbSu26dMRFdrCIiDwFdgMLAcqC2p2M1bj0mrOfVqnrU030LmI8ZaNmiJzAJKCIi32MGcPdbrB8Ia4e9PvAL0CrItpCYsAFtgRKqejIEdQcgIsWAUqo6zRvQRanqYW9zOHMMhPxcHQ6HI1w4UyJHukVEfsTYfN+jqhW8H//5IXDOXKmqlUSkHvAmZgXhRVW92rJOOKPDZAVeItmfYTIm4ZnVGXAvj0ZNYIGXI6EM8KqqWrVh9+n4ogSJSBZMpmqrIUy98Ku1MTPOC1R1r836PY1XVbWHiAwMstlqbgZPL9KXwyDUePdsJ1XdE2KdhzGrfblVtaQ3+O2vlhOp+ekVAooRGGlpdii0HA6HIy1xKwaO9ExJVb3NS2qEqh6X0NjG+DpNLTCdi9Ei0jMEOntF5C4Cs8Lajvfvo4WaDLpJWXRF5FaMM61NTqjqCRFBRDJ7PhulLWuAWVn5TURGeu/bYKLfWENEpnsdy/FByqyhqj28Px8KU4d9s4hMwjjx/2I7gVoK8gPrRWQRgT4Gtp3eHwdqAb959f8hIvksawBJq1O3AWtJflYoJkyvw+FwZCjcwMCRngmXzXe8iHyOSQL1lhfLPiIEOg9gssJ+QHJWWKuzw368QOpBQLCyi2WHiOQCRmGiSO0n2ZnWGqr6vojMJDkvw/2qusxG3d7qQ1bgchG5jGT79FigoA2NMxCuDntpjDnR48DXIjIOGKqqc0Og1ePcu1jhH1U96ZsnEJEoQheJqA3GhDFk/iYOh8ORXnCmRI50i4g0BboD5TBRTuoC96nqTMs6WTHhMFd5M49xQEVVnWJTJxyIyA3AjUB7TIfTRyxQTlVrhVC7PpAT469hxe7ac2w+IzZC13qOzU9iBgHxJA8MDgFfqmq/i9U4g24MpsN+O8avJZQddp/mZcBHQAdVjQyVzln0rSQeE5G3gQPAPZiEao8Ba71VMquIyETgVrWUFNDhcDjSM25g4EjXhMPmO9SIyMecZTZTVTtb1KoMVAF6Aa/4bToMzFDV/ba0woEXslYx339RYL/3dy5gm83IVSLSyXKUowvRDmmH3Ru03QbcACwCflTV4bZ1zuM4rCQeE5MZ/UGMD41gfGi+CsWqi4gMByoD0wk0j7J23zocDkd6wQ0MHOmajOD0JyL3en/Wxax++GbybwWWqOpTIdCMDlWs+rRARPoDY1R1gvf+BqCJqnazrFMB8x35h179zqZGCr2Qd9i9wdVyTBK6Mb7ITmmBrZj/IpIN49+S6L2PBDKr6rGLrTuI1r3BylX1W9taDofDkda4gYEj3eLn9LcGv5joIXBkDAsiMgO43tdh95JOTVHVhiHQKgX0JnUn10pyuHAjIktUtXqKssWqWsOiRg+gAeaaTcB01ueqajtbGin0wtJhF5FYVT0UirovFIsDgwWYgeER7312zL10zcXW7XA4HP+fcc7HjvRMRnP6KwjkAHx28dkJnXPrQIwj6AdAQ0w8/ks56dNeEekODMaYFt2F/YhO7TAmI8tU9X4RyQ98ZVnDn8ph6rAX8KI55ffC/lYCblLV18OgnRJbbTCLv82/qh7xfIWsIyJ1MTkufCuXgsUM7A6Hw5GeCEXkFYfDFpuA6LQ+CIv0AZaJyDci8g2wFJM3IRTEqOp0zKrgVlXtSfizz9rkDiAvMNJ75fXKbHJcVf8FTotILLAHCGXnr4CITBeR1QAiUskb/NjmS0xEqlMAqroS4/AcEkSkmIg08f6OEZEcfpttJR47KiJJKw8iUh04bqnulHwNvI+JiFUTqOH973A4HBkOt2LgSM8cA5aLSIZw+lPVgV6EE1/itOdVdZdvu4iUV9U1luROeA6af4jIE5hoOyGJ8x4OvOhDXc60XUQ+VtVOFymz2Au9+iUmsd4RYOFF1nk2vgSeAT4H02EXkR8A2zP5WVV1YYoUIKctawCBiceAkpiM2P3xMmGr6mpLUk8CP4mILzRuHMbsMBQcVNWJIarb4XA40hVuYOBIz4zxXhkGbyAw+gybB2HCVtrgSUxs/s7AaxhzoqBOlBmEuhdbgao+5v3Z38svEOvNroeKcHXY93o5QHz5QNoBCSHQgTAlHlPVRV6W7dIY0571IXS2nyEi7wAjCJygWBoiPYfD4Ugz3MDAkW75fxj1w5oPgKou8v48gvEvcJwDEWmLSTR2UFW3iEguEWmjqqNCJBmuDvvjwBdAGRGJBzYDHUKgAyFOPCYijVT1FxG5OcWmUiKCqo6wpeWHb4XP39FdubRN8xwOhyMobmDgSLf8P3T6s9mBmopJynTAe38ZJnlWM1saGZAeqjrS90ZVD3iRikI1MAhph11Euvq9nQDMwPiVHQVuwdjN22aWiLwIxHgJCh8Dxlqsvz7wCyYxXEoUM6tvlVBEDXM4HI70ihsYONIzXwNPYey9E9P4WC41LvcNCgBUdX8oTDrSETZWW4IFY7D+jAxjh93n9Fsa4yw7GnOd7gZClQvkeUzisVXAI5jzsxbZSVV7eH8+5MthEGpEJCcmwtd1XtEsoJeqHgyHvsPhcIQTNzBwpGf+vzn9nbRY178iUlRVt4GJFIPFFYm0wosWpKp6OMWmjyxUv1hE3gc+wVyrTphBqW3C0mFX1VcBRGQKUM13zUSkJ/CTLZ0UxAADVPVLTyvSK7OdeGyz5wfyI8b8K5RtewCwGmjvvb8bEw44pTmTw+FwXPK4BGeOdIuI9AEiySBOf2IMrzsAJVS1l4gUBQqoqvXINyLSHGOmMssrug7oqKqTbWuFAxGpgemM5cB0og8AD6iqtY67l033ZaCJVzQFeCOEicemALf4ddhzAD+panPLOusxORP+8d5nBlaoahmbOl7dYUk8JiIxGHOi2zEO++MwpnJzbep4WstVtcq5yhwOhyMj4FYMHOmZjOb09ykmg3MjoBdwGBhOCGKiq+okL857bUxH+ilV3evbbjk0ajgYADymqnMARKQeZqBQyZaANwB4/kzbLYVE9acogatEJ4HiFuv3MQhY6CU5U6AtECrH/rAkHlPV45iM0cM8/5mPMIPgSNtawHERqecbdHi+T6HKmeBwOBxpihsYONItGdDp72pVrSYiyyDJ7j9TqMS8gcC4M2y2GRo1HBz2DQoAVHWuiKQ0Jwo1Fx0SNQVh6bCr6hte/oxrvaL7VXWZbR2PoyJSzbeqF8rEYyJSH5O74AZgEcmmPrb5H/Ct52sAsB+4L0RaDofDkaa4gYEjXSMiLYDyQBZfmar2SrsjuihOeTbXvvCUeTErCGmBtdCoYWKhiHwODMFcv9uAmb7st5eieVk4O+ze9QnHNQpL4jER2Qwsx6waPBMqcy8AVV0OVPb8W1DVQ6HScjgcjrTGDQwc6RYR6Y9J0tUQE9mkHaHNRBtq+gIjgXwi8gbmfF5Oo2O51JyLfPbcPVKUX8MlbF4Wxg57WAhj4rHK4eqgi8ibwNspQv92U9Xu4dB3OByOcOKcjx3pFhFZqaqV/P7PDoxQ1evT+tj+K16nqTGm0zRdVdel0XEsVdVLyZQozRGRZapaNa2PIz1ylsRjANYTj4nIVcBnQH5VrSAilYCbVPV1mzqeVqrv3d0/Docjo+JWDBzpGZ9t8jERKQj8DVyRhsdzUYjIIFW9G1gfpCzc2AyNGnJEJA9mtaAeZoVgLiaW/N8h0AplSNSMSrgTj30JPAN8DqCqK0XkB8D6wACIFJHMflGdYoDMIdBxOByONMcNDBzpmXEikgt4m+R48taSJaUB5f3feP4G1UMhdK7QqKpaOxS6IWQoJsb/Ld77DpgY9k3O+IkLJGVIVBEJCImqqt/Y0spopEHisayqutA08yROh0hrMDBdRAZiBjkPELqoTg6Hw5GmOFMiR7rFm5n7H8Y5U4E5wGeqeiJND+wCEZEXgBdJTvTk682cBL5Q1RdCoPkZXmhUVS3r2UVPUVXroVHDgYgsUdXqKcoWq2qNM33mP2isBB5PERL1U1W1FhI1oyMi24CQJx7znLafwOR9qCYi7YAHVfWGEOk1xwxCBXMfXZL5QBwOh+NcuIGBI90iIsMwsf4He0V3ALlUNVRhCUOKiPQOxSDgDFpLfaFRffbRIrJCVSuHQ982IvIusBgThQaM43Z5v5lqGxrzVLXuucocZyZcicdEpAQmgd81mPChm4EOqrrVps55Hst8Va0Tbl2Hw+EIBW5g4Ei3BOvIXoqdWxEpo6rrfaE1UxKKUJsi8hum07TIGyDkxcx0XpLOs17OgmyAz0wlEvCFqFRVjbWg8QEmCpZ/SNT9mCR0l2RI1LTEL/FYB1W1knhMRLqmKIoBIvDagqq+b0PnAo/JOaU7HI4Mg/MxcKRnlolIbVVdACAiVwPz0viY/gtdgY7Ae35l/iPyUITaTE+hUS8aVc0hIrmBUgTmtJhlUSZDhkQNN//X3v2G6lnXcRx/f9wsJ6wyeqAgKkksIqVWqwhEzIxB9WBpFoQPpKI/PhD682CxwGERQQRB9EdDij3TUGcQtdRoD6IW5WgSQg+GkQ1ioExXayu+PbiuO87Ozr2Fu677d59r7xcczn732fh9BxvnfO/r9/t8Rx48trn/vIVuYvheuuM9d9DdQWnBd9ckTYZPDLR0khyi+2Z7Md0PAH/p11cDf6qqNzcs72VLcjvws6o6luTLdEct7h3rnehliUYdQpJPAHcDV9INtnoX8OuqurlpYTrNqsFjj401eCzJPuDWWXJUks109w22j7HfOWoxulTSZPjEQMvoA60LGMmuqnqwv9R6C90ThO8C7xx6oyWLRh3C3XTvEP+mqm7qm57dQ26wyEjUCVvU4LGrOD1y9yRwzQL2Xct6myIuSXPZGGjptLhAuCCz8/HvB75XVXuT3DPSXguLRl2QE1V1Igl9pvwzSbYMvMfokagXgMuTPML4g8f2AAf6vQrYwYgRokmuBt5QVY/3F6w3rphzsV6bbUk6w0WtC5AuIM8l+T7dmeufJnklA/8fTLKzv6h7fZJjSV7s13+nO4+9Xv21n2nxKPCLJHuBvw28x2ur6t6qOtx/fAV4zcB7TN39wE7gFHSDx+gSigZVVV8F7qS7HP4CcGdVfW3ofQCSfBL4Mf0wNbrjbI+uqOXpMfaVpBa8YyAtSJJLge3Aoar6c5IrgOuqat8Iey0sGnXR+sutr6a7rzHYBOdFRKJOXZLfVdW2VTG5B6vqLef6s8sqyUHgHcBvV/ydDlXVdW0rk6TheZRIWpCq+gfw8Ir1EeDIkHvMolGBh9aKR51C5ObASUQrfYouQWpPv94AHO8jMgeJRL0AHE1yLX1STz94bNB/4w38q6pOzqYsJ9mISUSSJsrGQJqWFtGok7CgSNSpu4tu8NgbkzxHP3isbUnn7VdJvgRsSnIL8FngJ41rkqRReJRImqBFR6NOgZGoL98yDh4bSpKLgI8D76NLIPo58IPym6ekCfLysTRNu/qmYBaN+kO6aFTNN4tEfbaqbgLeChxtW9K6sbn/eDvwGeAyuovbnwbe1LCuIWwCHqiqD1fVbcAD/WuSNDk2BtI0nRGNCryiYT3rwYmqOgH8LxKVbsCezqGqdlfVbuB1wNaq+kJVfZ4uIvfKttWdtyc4vRHYBDzeqBZJGpV3DKRpmkWjvhf4+hjRqBO0OhL1eYaPRJ26ZRo8NpRLquql2aKqXuoTxiRpcmwMpGm6nS4a9RtV9UIfjfrFxjUttara0f/yniS/pI9EbVjSerTQwWMLcjzJ1tn9nCRvA/7ZuCZJGoWXjyVJg+ljcm/ol/ur6qmW9ZyvJNvopmLPnh5dAXykqn7fripJGoeNgSRJZ5HkYrr7JgGeqapTjUuSpFHYGEiStEqS91TVk0k+tNbXq+rhtV6XpPXMOwaSJJ3pRuBJ4INrfK1YMcVckqbCJwaSJM2RZENV/efcv1OS1j/jCyVJmu9wkvuS3JwkrYuRpDHZGEiSNN8WuoFmd9E1Cd/uJ4pL0uR4lEiSpP9DksuAbwEfq6oNreuRpKH5xECSpLNIcmOS7wB/AC6hGyAoSZPjEwNJkuZIchg4CDwIPFZVxxuXJEmjsTGQJGmOJK+qqmOt65CkRfAokSRJ812e5IkkTwMkuT7JrtZFSdIYbAwkSZrvfmAncAqgqv4IfLRpRZI0EhsDSZLmu7SqDqx67d9NKpGkkdkYSJI039Ek1wIFkOQ24EjbkiRpHF4+liRpjiSvB+4D3g08Dxymm2PwbNPCJGkENgaSJK2S5HOrXtpE95T9OEBVfXPhRUnSyDa2LkCSpCW0uf+8BdgG7AUC3AHsb1WUJI3JJwaSJM2RZB9wa1W92K83Aw9V1fa2lUnS8Lx8LEnSfFcBJ1esTwLXtClFksblUSJJkubbAxxI8ghdMtEO4EdtS5KkcXiUSJKks0iyFbihX+6vqqda1iNJY7ExkCRJkuQdA0mSJEk2BpIkSZKwMZAkSZKEjYEkSZIk4L8X3rcvinAiRwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 936x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(13,9))\n",
    "sns.heatmap(train_corr, annot=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-25-986031138159>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mtrain_save\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'train'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtrain_X\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mtrain_save\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'click'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtrain_Y\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0mdump\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtrain_save\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'train.joblib_dat'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mcompress\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/joblib/numpy_pickle.py\u001b[0m in \u001b[0;36mdump\u001b[0;34m(value, filename, compress, protocol, cache_size)\u001b[0m\n\u001b[1;32m    498\u001b[0m     \u001b[0;32melif\u001b[0m \u001b[0mis_filename\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    499\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'wb'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 500\u001b[0;31m             \u001b[0mNumpyPickler\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprotocol\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mprotocol\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdump\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    501\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    502\u001b[0m         \u001b[0mNumpyPickler\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprotocol\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mprotocol\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdump\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/pickle.py\u001b[0m in \u001b[0;36mdump\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    407\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mproto\u001b[0m \u001b[0;34m>=\u001b[0m \u001b[0;36m4\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    408\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mframer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstart_framing\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 409\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    410\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mSTOP\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    411\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mframer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mend_framing\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/joblib/numpy_pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    290\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    291\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 292\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mPickler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    293\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    294\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    474\u001b[0m         \u001b[0mf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdispatch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mt\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    475\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 476\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    477\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    478\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/pickle.py\u001b[0m in \u001b[0;36msave_dict\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    819\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    820\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 821\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_setitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    822\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    823\u001b[0m     \u001b[0mdispatch\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdict\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msave_dict\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/pickle.py\u001b[0m in \u001b[0;36m_batch_setitems\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    845\u001b[0m                 \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mv\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtmp\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    846\u001b[0m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 847\u001b[0;31m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    848\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mSETITEMS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    849\u001b[0m             \u001b[0;32melif\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/joblib/numpy_pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    290\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    291\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 292\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mPickler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    293\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    294\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    519\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    520\u001b[0m         \u001b[0;31m# Save the reduce() output and finally memoize the object\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 521\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave_reduce\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0mrv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    522\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    523\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mpersistent_id\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/pickle.py\u001b[0m in \u001b[0;36msave_reduce\u001b[0;34m(self, func, args, state, listitems, dictitems, obj)\u001b[0m\n\u001b[1;32m    632\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    633\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mstate\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 634\u001b[0;31m             \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    635\u001b[0m             \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mBUILD\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    636\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/joblib/numpy_pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    290\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    291\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 292\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mPickler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    293\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    294\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    474\u001b[0m         \u001b[0mf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdispatch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mt\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    475\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 476\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    477\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    478\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/pickle.py\u001b[0m in \u001b[0;36msave_dict\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    819\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    820\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 821\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_setitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    822\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    823\u001b[0m     \u001b[0mdispatch\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdict\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msave_dict\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/pickle.py\u001b[0m in \u001b[0;36m_batch_setitems\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    845\u001b[0m                 \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mv\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtmp\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    846\u001b[0m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 847\u001b[0;31m                     \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    848\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mSETITEMS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    849\u001b[0m             \u001b[0;32melif\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/joblib/numpy_pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    290\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    291\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 292\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mPickler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    293\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    294\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    519\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    520\u001b[0m         \u001b[0;31m# Save the reduce() output and finally memoize the object\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 521\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave_reduce\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0mrv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    522\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    523\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mpersistent_id\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/pickle.py\u001b[0m in \u001b[0;36msave_reduce\u001b[0;34m(self, func, args, state, listitems, dictitems, obj)\u001b[0m\n\u001b[1;32m    632\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    633\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mstate\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 634\u001b[0;31m             \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    635\u001b[0m             \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mBUILD\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    636\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/joblib/numpy_pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    290\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    291\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 292\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mPickler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    293\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    294\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    474\u001b[0m         \u001b[0mf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdispatch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mt\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    475\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 476\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    477\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    478\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/pickle.py\u001b[0m in \u001b[0;36msave_tuple\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    749\u001b[0m         \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mMARK\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    750\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0melement\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 751\u001b[0;31m             \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0melement\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    752\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    753\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mid\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmemo\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/joblib/numpy_pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    290\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    291\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 292\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mPickler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    293\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    294\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[1;32m    474\u001b[0m         \u001b[0mf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdispatch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mt\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    475\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 476\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Call unbound method with explicit self\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    477\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    478\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/pickle.py\u001b[0m in \u001b[0;36msave_list\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    779\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    780\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 781\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch_appends\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    782\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    783\u001b[0m     \u001b[0mdispatch\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mlist\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msave_list\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/pickle.py\u001b[0m in \u001b[0;36m_batch_appends\u001b[0;34m(self, items)\u001b[0m\n\u001b[1;32m    806\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mAPPENDS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    807\u001b[0m             \u001b[0;32melif\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 808\u001b[0;31m                 \u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtmp\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    809\u001b[0m                 \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mAPPEND\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    810\u001b[0m             \u001b[0;31m# else tmp is empty, and we're done\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/joblib/numpy_pickle.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    287\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    288\u001b[0m             \u001b[0;31m# And then array bytes are written right after the wrapper.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 289\u001b[0;31m             \u001b[0mwrapper\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite_array\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    290\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    291\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/joblib/numpy_pickle.py\u001b[0m in \u001b[0;36mwrite_array\u001b[0;34m(self, array, pickler)\u001b[0m\n\u001b[1;32m    102\u001b[0m                                            \u001b[0mbuffersize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbuffersize\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    103\u001b[0m                                            order=self.order):\n\u001b[0;32m--> 104\u001b[0;31m                 \u001b[0mpickler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfile_handle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mchunk\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtostring\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'C'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    105\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    106\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mread_array\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0munpickler\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "# from joblib import dump, load\n",
    "# train_save = {}\n",
    "# train_save['train'] = train_X\n",
    "# train_save['click'] = train_Y\n",
    "# dump(train_save, 'train.joblib_dat',compress=0)"
   ]
  }
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